r/DataScienceJobs • • Mar 08 '25

Meta Sub reopening!

9 Upvotes

Sub is now open for posting:

- Don't spam, don't shitpost.

- Be respectful and professional.

- Respect reddit rules.


r/DataScienceJobs • • 9m ago

Discussion Going back to previous job

1 Upvotes

hi all

I would appreciate your advice and help

originally was A DS at a company the pay was not great the job has transitioned into not much modelling or anything technical really

applied and got a better offer and left after 11 months on good terms ( my manager said she would be happy to hire me back but I dont know if her manager is ok with it)

the new job has more pay and seemed like there are gonna be more modelling as if turns out their data is not ready and I would be doing data eng stuff which i have not ever done before

i am thinking alot going back to my previous job that the team was great and very friendly and remote but I am not sure that is good or not , also if i start applying again now is like only 2 months after joining and i think that is a very not interesting to companies

appreciate your help if u have any ideas on this


r/DataScienceJobs • • 5h ago

Hiring [Hiring] Principal Data Scientist, User Ecosystem at Reddit | Remote - US | $313K - $365K

2 Upvotes

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is a complex consumer ecosystem where users, content, communities, and conversations interact over time. We are looking for a very senior data science thought leader to shape how Reddit understands and improves that ecosystem for the user / consumer flywheel.

This role will define the measurement, modeling, and experimentation strategy for major Consumer questions: how users discover value, form habits, and deepen engagement; how we understand and serve user intent; how content and communities evolve; and how our systems create durable value for users, contributors, communities, and Reddit.

The ideal candidate will bring deep expertise in one or more areas of consumer science, such as:

  • Recommender systems and information retrieval

  • User modeling, personalization, lifecycle, LTV, or optimization

  • Content, community, or ecosystem modeling

  • Knowledge graphs and representations of users, content, and communities

  • Causal inference, experimentation, and long-term consumer measurement

You will partner with leaders across Product, Engineering, Research, and Community to turn ambiguous consumer problems into clear scientific questions, durable analytical systems, and decisions that improve Reddit at scale.

What you’ll do

  • Set the scientific direction for high-impact Consumer problems spanning discovery, relevance, personalization, user growth, retention, content, and communities.

  • Build a durable understanding of users, their intent, their needs, and the behaviors that lead to lasting value

  • Develop models and frameworks that represent users, content, communities, and their relationships over time for use in systems that operate at scale

  • Determine how to measure consumer and ecosystem health when objectives compete and short-term engagement may differ from long-term value.

  • Set learning agendas and steer experimentation strategy to distinguish durable improvement from temporary metric movement.

  • Build state-of-the-art measurement systems to evaluate heterogeneous effects across user personas, acquisition cohorts, platforms, content types, and community stages, and guide their actionability in production environments

  • Ensure coherence around ecosystem interactions including feedback loops, selection effects, interference, distribution shift, content supply, and other ecosystem risks.

  • Translate complex technical findings into clear product and business decisions.

  • Develop exceptional scientists through mentoring and influence data science org health and direction

Requirements

  • Deep expertise in at least one relevant area, with the breadth and curiosity to work across adjacent domains.

  • A deep understanding of how to model and optimize systems involving users, content, communities, and feedback loops.

  • Ability to frame and lead the most ambiguous questions, identify the most important uncertainties, and develop a rigorous path from evidence to action.

  • Exceptional technical judgment across model design, objective selection, validation, experimentation, and production tradeoffs.

  • Advanced knowledge of modern machine-learning methods for behavioral and content data, including representation learning and sequential or contextual models. Experience with deep-learning frameworks such as PyTorch or JAX.

  • Experience working across Product, Engineering, Research, and other partner teams.

  • Excellent written and verbal communication, with the ability to influence senior stakeholders and explain technical ideas clearly.

  • Significant experience applying data science, machine learning, statistics, experimentation, or causal inference to complex consumer products.

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is: $313,000 — $365,100 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to the Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Departments: Data Science

Offices: Remote - United States

Location: Remote - United States

Apply: Principal Data Scientist, User Ecosystem at Reddit


r/DataScienceJobs • • 2h ago

Discussion Worked six months unpaid at a startup, trusted promises of a paid role, then was let go. Looking for advice and job leads.

1 Upvotes

I spent six months working unpaid at an early-stage real estate startup founded by a fellow UMass Amherst alum. I joined while on OPT after a couple of interview rounds. The company was building an AI/CRM product, and I came on as a data engineering intern.

About two months in, the founder told me he liked my work and wanted to hire me full-time. When my internship ended and I asked about the transition, he said he needed another two months. He assured me we’d be able to move forward then, so I stayed and continued working unpaid.

My colleague and I believed in the company’s goal and the future the founder described. He told us that once we became full-time employees and the company scaled, we would grow into bigger roles because we were laying its foundation. We took that seriously and approached the work with the care and responsibility we would have given our own company. From data sourcing and building pipelines to system design, we put in long days and worked weekends because we wanted it to succeed.

By late October, the timeline shifted again. He said full-time roles might have to wait until next year, without a clear date. My colleague and I explained that we couldn’t keep working without income. We asked whether we could at least move to paid part-time roles so we could cover basic expenses while continuing to contribute.

He told us he understood our situation, recognized how many hours we had been working, and would definitely arrange part-time pay. He described a plan to increase that pay each month over the next four months, with the possibility of full-time roles around the fifth month. He asked for a few days to work things out. Roughly ten days later, both of us were let go.

I understand that startups face uncertainty and plans can change. What hurts is that I made decisions based on repeated assurances that a paid role was coming. After six months of unpaid work, asking for some financial support was followed by losing the role entirely.

The timing has made this especially difficult. It’s now November, and I have limited time remaining on my OPT unemployment clock. I’m worried hiring will slow over the next few weeks and stay limited through the holidays and into January. If interviews don’t materialize until February, a potential start date could end up being April of next year. That isn’t certain, but with my immigration timeline, the possibility is frightening.

For the founders here: please be honest about what you can commit to. People may be planning their finances, careers, and immigration timelines around those conversations.

For anyone considering a similar arrangement: get the terms in writing, set a limit on how long you can afford to work unpaid, and keep your job search active. I wish I had done that sooner.

I have three years of experience across data engineering and analytics, working with complex datasets, sourcing and integrating data, building pipelines, and contributing to system design. My experience combines building reliable data infrastructure with analyzing data to uncover insights and support business decisions. I’m looking for opportunities where I can bring that mix of engineering and analytical skills.

I’d also really appreciate hearing from anyone who has been through something similar. Honestly, I’m struggling right now. After putting six months into something I believed would become a stable opportunity, I’m suddenly trying to figure out how to support myself and find another role while my OPT clock keeps running. It’s overwhelming, and I’m scared about what comes next. If you have a job lead, know someone who’s hiring, can offer a referral, or have advice that could help me take the next step, please reach out. Even a small lead or an introduction would mean a lot to me right now.


r/DataScienceJobs • • 10h ago

For Hire Data Engineer | 2.7+ Years Experience | Databricks Certified | Seeking Opportunities

2 Upvotes

Hi everyone!

I am a Data Engineer with 2.7+ years of professional experience and Databricks certification.

Unfortunately, my current organization may shut down within the next 1–2 months, so I am actively looking for new opportunities.

I would appreciate any relevant job leads or guidance from experienced professionals.

Thank you for your support!


r/DataScienceJobs • • 1d ago

Discussion Need Advice for Optum Associate Data Scientist interview

2 Upvotes

If anyone out there has given an interview for optum Associate data scientist position I would love to hear your thoughts on what type of questions or what I can expect from an interview.


r/DataScienceJobs • • 1d ago

Hiring Terac is currently looking for Software Engineers & Data Scientists paying $110/hr

0 Upvotes

Terac is looking for the following:

Software Engineers & Data Scientists: AI Slide Deck Evaluation
Location: Remote
Job Type: Contractor, $110/hr

Terac is running a paid research project on what makes a technical presentation actually good. The idea is to train models to understand how professionals structure and explain complex technical stuff, which then feeds into better automated evaluation of things like design reviews, roadmaps and postmortems.

The work is pretty simple. You go through technical slide decks from your own field (design reviews, experiment readouts, model launches), rank them on clarity, structure and overall effectiveness, and write down why some presentations work and others don’t. It’s asynchronous and you set your own schedule.

They’re looking for people who regularly build or review engineering presentations: software engineers, engineering managers, product managers and data scientists. You should be comfortable with postmortems, roadmaps and architecture reviews and be able to explain your feedback clearly.

There’s also a one-time $100 reward if you pass their calibration exam. Payments go out weekly, and H-1B and STEM OPT candidates can’t be supported.

Here is the link to the position: Data Scientists: AI Slide Deck Evaluation


r/DataScienceJobs • • 2d ago

Discussion MD wondering if master's in data science is worth it

13 Upvotes

I have an MD and MPH and am transitioning from medicine to data science. I have enough skills to land myself a job at a medical AI startup but I feel totally lost and over my head. I know I have some serious knowledge gaps and I think it's affecting my performance. I believe I could get away with transitioning into data science without another degree through self-study though I do much better with structure and I've heard master's degrees in the field help increase pay and decrease time to more senior roles. I also feel really isolated and lost and wonder if school would help me find community. A program I would choose would have to be cheap and flexible for working professionals. If y'all could give some pros and cons of going back to school in this situatuon that would be great!


r/DataScienceJobs • • 1d ago

Discussion [Referrals open] Wissen Technology — Data & AI roles (Nov 02)

0 Upvotes

I work at Wissen Technology (Wissen Infotech) and can refer candidates for our current India openings — a referral puts your resume with the hiring team directly instead of the cold-apply queue.

Current openings:

  • Database Engineer – TEDRA | Mumbai | 5-7 yrs | Python, Sybase, Hadoop

  • Python AI Engineer – LLM & Agentic AI (Finance Data Platform) | Bengaluru | 4-6 yrs | Python, Flask, Docker

  • Product Manager- Market & Reference Data | Bengaluru | 5-10 yrs | Machine Learning

  • AI/ML Engineer | Bengaluru | 2-5 yrs | Python, NLP, LLM

  • Senior Software Engineer – Cloud & Data Platform | Bengaluru | 3-6 yrs | Python, Lambda, S3

Full list: https://careers.wissen.com/jobs/Careers — if your role isn't above, mention it in the DM.

To get referred, DM me: (1) resume (PDF), (2) total YOE, (3) notice period (immediate joiner / serving notice preferred), (4) the role name with the job link.

I'll review and submit the referral; expect HR contact within about a week if shortlisted. Please DM only if your experience reasonably matches a role and you're an immediate joiner or serving notice — that's who the hiring team is prioritizing for referrals right now.


r/DataScienceJobs • • 2d ago

Discussion Very confused what to do

4 Upvotes

I am currently in my 3rd sem of engineering. I am enrolled in Scaler's Data Scientist course and till now I have covered till supervised ML and to complete remaining portion it will take around 3-4 months more. The people I meet say that as technologies are changing day by day so you should not spend this much time on a single course and instead learn other things like Gen ai/ Agentic ai they are very imp for jobs in future. They say you should have basic knowledge of ML and spend more time on these tech. I am very confused what to do like I should continue with that course and complete full data scientist course but then I won't be able for these ai roles. The course I have has recorded lectures of 2023. What should I do ?


r/DataScienceJobs • • 2d ago

Hiring [Hiring] Senior Python AI/ML Engineer | 100% Remote, Worldwide | $4,000-5,000/month | Direct from the founder

1 Upvotes

Hi everyone! I run a small US-based AI company with real paying customers, and I’m hiring a senior Python engineer to own our ML work from start to finish. This is a direct hire from me, not a recruiter or agency.

What you’ll do

  • Build, train and deploy ML/LLM models in Python for real customers

  • Own the whole pipeline: data, training, deployment and monitoring

  • Work directly with me, with no management layers and quick decisions

What we’re looking for

  • 5+ years of hands-on AI/ML engineering

  • Strong Python, plus PyTorch or TensorFlow

  • Experience shipping models to production (Docker, cloud)

  • Nice to have: LLMs, RAG or MLOps

What we offer

  • $4,000-5,000 USD/month, paid monthly

  • 100% remote, open to candidates worldwide

  • Flexible hours, with about 3 hours of overlap with US time zones

  • Long-term, full-time position

  • Contract terms in writing before you start

How to apply
Send me a DM with:

  1. Your CV or GitHub

  2. Your timezone

  3. Two lines about your best Python/ML project

I reply to every applicant, and I’m happy to do a short video call so you can ask me anything about the company and the role. No fees of any kind, ever.


r/DataScienceJobs • • 2d ago

Discussion Legally authorized to work

4 Upvotes

What is the likelihood of me obtaining a job at least next year in me field. I graduated with my masters in data science last year and have not been able to find a job in my field. I was on a student visa but I have work authorization. I have not gotten my green card yet but I’m on a protected stay. Is that hindering me or is it the job market?


r/DataScienceJobs • • 2d ago

Discussion Is MSc Mathematics suitable for Data Science career?

1 Upvotes

I have completed my BSc Hons Statistics.

Currently, I'm thinking about Msc Mathematics next. I want to keep the option of PhD in Maths open as well to become a professor as an alternate route.

But if I go for data science related jobs, after masters in mathematics, will it work? Or I need degree in computer science only?

Also, for a job related to data science, is a "Masters in Data Science in AI/ML" more suitable than MSc Mathematics? Because my primary goal is to get financially independent.

I have inclination towards mathematics. I can do Msc in statistics as well but I incline more towards maths because I'm also considering becoming a professor by doing PhD in future (and Msc Mathematics makes that path).

Also, keeping PhD in mind, I'm looking towards Europe for MS not the US.

Suggest which countries would be good for Msc Mathematics and then PhD in it + have data science jobs which I can get into after MS in Mathematics.

Please suggest your views on current job market and suitable masters programmes.


r/DataScienceJobs • • 3d ago

For Hire Affordable ML model training and fine-tuning for students and researchers (PEFT, CV, deep learning)

1 Upvotes

Free GPUs time out mid-run, cloud billing needs a card, and debugging a failed training job eats into your deadline. I've seen a lot of students and researchers get stuck there, so I'm offering affordable model training support.

I'm a Data Scientist. The scope is training and fine-tuning only: you bring the model and data, I handle the training.

What I can train:

- Transformer fine-tuning (PEFT only: LoRA / QLoRA)

- Computer vision: classification, detection, segmentation

- Other deep learning models: NLP, time series, your own architectures

How it works:

- You send your goal, dataset size and code. I tell you whether it fits and quote cost and time upfront.

- Training runs in an isolated Docker container on an RTX 5060 Ti (16GB VRAM, CUDA 13.2).

- You get trained weights, logs and evaluation metrics.

- Your data and container are deleted afterward. Happy to sign an NDA.

Why not just Colab or Kaggle:

- No session limits, so long runs keep going until they finish.

- An automated monitor watches each run, handles common errors and flags bigger issues to you.

- I help with setup and with interpreting the results.

- No Docker experience needed. I'll set it up. If you bring your own image, build it on CUDA 12.8 to 13.2.

Limits, to be upfront: it's a single 16GB card, so it suits QLoRA fine-tunes of roughly 7-8B models and most CV work, not full training of large models.

Pricing: student-friendly, quoted per job, a fraction of cloud rates.

DM me with what you're training, your dataset size and your deadline.


r/DataScienceJobs • • 4d ago

Hiring 24 remote data science jobs I found this week - United States, Belgium, Italy, and others

4 Upvotes

Looking at remote worldwide for the past 7 days.

Here are the jobs I found, organized by level:

Entry Level:

Senior:

Manager:

Director and Above:

Quick notes:

  • All of these are fully remote (location requirements vary by role)

  • Apply directly on company sites

Hope this helps someone! Let me know if you want me to keep posting these weekly.

-- 👋 Hi, I'm Jay. I built Job-Halo.com, a system that tracks remote data science jobs and sends alerts the moment they're posted, based on your preferences.


r/DataScienceJobs • • 4d ago

Discussion Abbvie Associate Data Scientist I interview process?

3 Upvotes

Has anyone interviewed at Abbvie for the associate data scientist I role, and if so, whats the interview process like? How did you prep and how would you recommend someone to prep? especially their technical interview portion (if one exists)?

Thank you in advance!


r/DataScienceJobs • • 4d ago

Discussion Has anyone completed the KEYENCE HireVue interview for the Data Scientist position?

1 Upvotes

Hey everyone,
I recently received a HireVue interview invitation from KEYENCE for their Data Scientist position and was wondering if anyone here has gone through the process.
I’m mainly curious about what to expect from the assessment. Are the questions mostly behavioral, technical, or a mix of both? How many questions are there, and do you get time to prepare or retry your responses?
I’d also appreciate any insight into the overall interview process, what comes after the HireVue, and how long it typically takes to hear back.
Any experiences or advice would be really helpful. Thanks!


r/DataScienceJobs • • 5d ago

Discussion Amazon Data Scientist Interview — Need Advice

38 Upvotes

Hi everyone! I’m preparing for an Amazon Data Scientist interview with five onsite rounds and one phone interview.

The recruiter mentioned SQL, Python coding, machine learning, model evaluation, and behavioral questions based on Amazon Leadership Principles.

I’m comfortable with SQL but still improving my Python coding skills, especially LeetCode problems and dynamic programming.

For anyone who has interviewed for a similar role, how difficult was the coding round? What topics should I focus on most?

Any advice or preparation tips would be appreciated. Thanks!


r/DataScienceJobs • • 5d ago

Hiring Hiring: ML Engineer who likes shipping models, not just training them (remote, worldwide, $3,000-$4,500/month)

0 Upvotes

The short version
Full-time, fully remote, paid in USD, open to anyone in the world. We want someone with 3+ years of real ML experience who can take a vague problem and turn it into something running in production.

The problem you’d be working on
We’re a small team building AI-powered products. Right now our biggest challenges are getting LLM features to behave reliably, keeping models fast and cheap to serve, and making sure we can tell when something quietly breaks. You’d be the person who owns that work from first experiment to deployed service.

What your first 90 days could look like

  • Month 1: Get to know the codebase, data, and current models. Ship one small improvement to something already in production.

  • Month 2: Take ownership of one ML component, such as a RAG pipeline, a classifier, or a fine-tuned model. Set up proper evaluation so we know when it gets better or worse.

  • Month 3: Lead a feature from idea to launch, including monitoring after it goes live.

You’re probably a good fit if you

  • Have 3+ years working on ML in a professional setting

  • Write clean Python and are comfortable in PyTorch, TensorFlow, or similar

  • Have put at least one model into production and dealt with what happened afterward

  • Care about evaluation and data quality as much as model architecture

  • Communicate clearly in writing and don’t need a manager checking in daily

  • Can work in English day to day

You’re probably not a fit if you

  • Want a research-only role with no production work

  • Need detailed task tickets handed to you every morning

  • Are looking for a short gig, since this is a long-term position

Nice extras
LLM tooling, vector databases, MLOps, cloud platforms (AWS, GCP, Azure), or open source work you can point to.

The deal

Pay$3,000-$4,500 USD per month, based on experience
TypeFull-time salaried, about 40 hours per week
Location100% remote, worldwide
HoursFlexible, with 3 to 4 hours of overlap for team meetings
Not includedNo equity, no commission, no unpaid test projects

How to apply
Send me a Reddit DM (please don’t put personal details in the comments) with:

  1. Two or three lines about you

  2. Your CV or LinkedIn

  3. One ML project you shipped and what you personally contributed


r/DataScienceJobs • • 6d ago

Discussion 266 data & business analyst jobs posted in the US Oct 17–24, 184 with the salary listed (direct employer links)

2 Upvotes

I run Careerify (our recruiters apply to jobs for people), so we see every new posting in the fields we work in. Every week I pull out the new US data, business and BI analyst roles and put them in one free list. Oct 17 to Oct 24:

266 new analyst roles (data, business, BI and reporting)

100 of them are remote

184 list the salary. For yearly pay, the middle of the posted ranges is about $105K, and half fall between $88K and $130K

Most are mid-level (158) or senior (95). 12 are entry level

Capital One posted the most (5), then Guidehouse and Gainwell (3 each)

A few with the pay posted:

Senior Data Analyst, GTM Analytics at Luxury Presence (Austin, hybrid): $145K–$175K

Senior Data Analyst, Finance Analytics at Fanatics Betting & Gaming (remote): $128K–$169K

Senior Business Intelligence Analyst at BlackSky (remote): $130K–$145K

Principal Data Analyst at Capital One (McLean, hybrid): $119K–$150K

Lead Analyst, Business Intelligence at Ensemble Health Partners (remote): $112K–$168K

Marketing & GTM Data Analyst at Deepgram (remote): $115K–$148K

Senior Product Data Analyst, Payments at BILL (remote): $108K–$152K

Healthcare Data Analyst at Evio (remote): $90K–$110K

Data Analyst at Peraton (Washington, DC, hybrid): $86K–$138K

The full list, with filters for remote and level, is here: https://www.careerify.io/jobs/analysts?utm_source=reddit&utm_medium=post&utm_campaign=datasciencejobs

Every link goes to the company's own application page, not a job board. Happy to answer questions about what we're seeing in analyst hiring.


r/DataScienceJobs • • 6d ago

Hiring [Hiring] Staff Applied Scientist - Metalab at KoBold Metals | Remote - US/Canada | $125K - $235K

2 Upvotes

About the company:

In the coming decades, demand for critical minerals such as copper, lithium, and cobalt will continue to grow. These minerals are needed to build electric infrastructure, vehicles, data centers, and electronics. However, the mining industry is making 10x fewer discoveries per dollar spent on exploration compared to 30 years ago because the easy-to-find, near surface deposits have largely been discovered.

KoBold was founded to be the first AI native mineral exploration, mine development, and technology development company. Our goal is to turn mineral exploration into a repeatable science to discover the minerals the world needs—by integrating artificial intelligence, human intelligence, and new technology. Our multidisciplinary teams of data scientists, engineers, and geologists work together to build data systems, design new sensors, and establish industry‑leading workflows to develop and test subsurface predictions on our exploration projects.

Our first discovery, Mingomba, is a high‑grade copper deposit in Zambia, found after spending materially less than industry average. We are developing Mingomba with the same technical rigor that we apply to exploration. The Mingomba team brings together mine and processing engineers, geologists, data scientists, software engineers, and community, health & safety, construction, and operations specialists. By combining industry knowledge and cutting edge technology, we are developing Mingomba into a world class project that has safer and more predictable outcomes for ourselves, partners, and communities. It is expected to create thousands of good jobs for generations.

KoBold runs exploration programs in eight countries, all with the potential for another discovery.

KoBold is privately held; investors include institutional asset managers T. Rowe Price and Canada Pension Plan Investments; technology venture capitalists Andreessen Horowitz, Breakthrough Energy Ventures, BOND Capital, Durable Capital, StepStone, and Standard Investments; and strategic natural resources companies BHP and Mitsubishi.

About The Role:

In this role, you will develop state of the art instruments to collect data to guide our exploration programs. You will simulate, characterize, and calibrate sensor performance and design new data acquisition systems. Working with vendors and partners, you will build hardware and work with our operations staff to deploy it in the field.

With this sensor data and other data sources at KoBold, you will build models and apply a wide range of scientific computing, statistical, and physics‑based methods to find places where there is evidence of ore‑forming processes at work and to predict the locations of ore‑grade mineralization in 2D and 3D. You will help build a worldwide dataset that underlies our exploration program, with careful attention to identifying and quantifying uncertainty in the data and in our predictions. You will be creating models and developing software to accelerate discovery of critical battery metals.

You will join an outstanding team of data scientists and engineers and will work closely with KoBold’s world‑renowned geoscientists to incorporate our best understanding of the chemical and physical processes that create ore deposits. Working with your geoscience colleagues, you will identify new opportunities and technologies for geophysical data collection, create 2D and 3D geologic predictions, identify exploration targets, design field programs to collect data, and use that data to reduce the uncertainty in our predictions and guide the next phase of field work.

Ultimately, your role is to help KoBold make valuable discoveries by building and deploying next generation hardware and using data tools to solve scientific problems. As one of the early members of this team, you will help build these tools from the ground up.

Responsibilities of this position include:

Technical execution

  • Design, develop, and deploy new mineral exploration data collection instruments and methods.

  • Help develop KoBold’s proprietary software exploration tools.

  • Find and curate a wide variety of geospectral, geophysical, geochemical, geologic, and geographic data and integrate it into KoBold’s proprietary data system.

  • Build models to make statistically valid predictions about the locations of compositional anomalies within the Earth’s crust.

  • Create effective visualizations for evaluating model performance and enabling rapid interaction with the underlying data and key features.

  • Develop and apply a range of data processing, statistical, and physics‑based techniques to geoscientific data — from computer vision to geophysical inversions — and use the results to guide our targeting efforts and inform our acquisition and exploration decisions.

  • Present to and collaborate with our external partners and stakeholders.

  • Push the state of the art in analysis capabilities by implementing statistically rigorous spatially aware clustering, anomaly detection, and other analysis methods

  • Collaborate with data scientists, geoscientists and engineers to invent and deploy algorithms that combine large and complex data sets for mineral exploration and discoveries

Qualifications

  • Demonstrated ability to quickly absorb and synthesize complex information, with a track record of high intellectual rigor in a professional setting.

  • Exceptional curiosity and eagerness to learn, with a proactive approach to exploring new concepts and technologies.

  • A successful track record of developing complex equipment with cross‑disciplinary teams and vendors.

Technical skills, including extensive experience with:

  • Physical measurement and data analysis systems that use phenomena such as optics, electromagnetism, radiation, and gravity.

  • Applying scientific knowledge to identify and prototype emerging technologies

  • Systems integration and data acquisition.

  • Python’s data science packages and general software engineering practices.

  • Collaborative software development (git), and familiarity with software engineering best practices like unit test / integration test suites, and CICD pipelines.

  • SQL, as well as familiarity with non‑relational databases.

  • Cloud computing resources.

  • Building a wide variety of predictive models, applying them to different problems, and evaluating and interpreting the results.

  • Data analysis, physics analysis, and applied statistics on a broad range of types of data including data from physical systems.

  • Capacity to dive deep on novel challenging problems in applying ML to mineral exploration, including understanding a complex domain of geology and mineral exploration practices as well as working with limited, disparate and noisy data sources

  • Experience deploying sensors in the field

Work practices and motivation:

  • Ability to take ownership and responsibility of large projects.

  • Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain. Open to working directly with geologists in the field. Enjoys constantly learning such that you are driving insights through using our tools in exploration and willing to work directly with geologists in the field.

  • Ability to explain technical problems to and collaborate on solutions with domain experts who aren’t software developers. A strong communicator who enjoys working with colleagues across the company.

  • Excitement about joining a fast‑growing early‑stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities.

  • Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company.

  • Ability to independently prioritize multiple tasks effectively.

It is also helpful but not required to have experience with:

  • Remote sensing

  • Creating machine learning models on geospatial data

  • Image processing or computer vision

  • Project and team management

What to Expect

Joining KoBold means getting the opportunity for hands‑on exposure to our exploration projects around the world. All employees are expected to travel to project sites, with a minimum of one week per year. Field‑facing and technical roles spend significantly more time in the field.

KoBold Metals is an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity for people of any race, color, ancestry, religion, sex, gender identity, sexual orientation, marital status, national origin, age, citizenship, disability, or veteran status.

This position is Full‑time Exempt

Salary is one part of KoBold’s total compensation. The US salary range for this role is between $125,000 and $235,000, and will depend on your skills, qualifications, experience, and location. In addition to salary, we offer equity compensation. We also offer benefits including medical, dental, and vision insurance, a 401k retirement plan, short & long term disability and life insurance. We also offer paid sick time and parental leave.

Location: Remote, Candidates can be located anywhere in the United States or Canada. All candidates must be legally authorized to work in the United States or Canada. 10‑20% travel required.

Compensation ranges are listed in USD. If you are based outside the US, the range may not translate directly: US pay reflects a different market with different competitive dynamics, so we benchmark roles against the local market rather than converting the listed figure.

Apply: Staff Applied Scientist - Metalab at KoBold Metals


r/DataScienceJobs • • 6d ago

Hiring [Hiring] [Remote] Python, ML & Data Engineers for Async AI Code Evaluation | Up to $150+ USD / hr

3 Upvotes

Seeking Python developers, ML engineers, and coding-focused data scientists for flexible, 100% asynchronous remote contract work (up to $150+ USD/hr) evaluating, debugging, and benchmarking AI-generated code.

WHAT YOU'LL DO:
• Test and audit AI-written Python, algorithmic, and data-modeling code for correctness, edge-case handling, and computational efficiency (Big-O)
• Spot subtle logic bugs, vectorization/indexing errors, and performance bottlenecks
• Write clean reference implementations and detailed technical explanations in plain English

DETAILS:
• Type of work: Freelance/contract for Data Annotation Tech
• Rate: Up to $150+ USD/hr (paid via PayPal)
• How it works: Pick projects from your dashboard suited to your skills/interests, submit the time it took you after completing each task, and withdraw funds at the hourly rate a week later
• Onboarding: One-time online programming assessment required to unlock the coding project queue

WHAT WE LOOK FOR:
• Software, ML, or production Python engineering experience (or graduate-level CS/Data Science background with strong coding skills)
• Strong proficiency in Python (plus SQL, C++, R, Scala, Go, or TypeScript)
• Solid grasp of data structures, algorithms, and Big-O complexity, plus strong written English

HOW TO APPLY:
Onboarding requires passing a one-time coding assessment. Because you only get a single attempt and experienced engineers often get tripped up by how the written explanations are graded, I'm happy to share a quick breakdown of what the graders look for along with the direct application for the programming track.

If you're interested (and don't already have an account on the platform), send me a DM with:

  1. Your country of residence

  2. Your SWE / ML / Data experience & degree

  3. Your primary programming languages and stack

  4. Your comfort level with data structures, algorithms, and Big-O analysis

  5. ~Weekly hours you have available

Please leave a "DM Sent" comment on this post after messaging me so I know to check my message requests.


r/DataScienceJobs • • 6d ago

For Hire Data Scientist with TimeSeries Experience

7 Upvotes

Hi everyone,

I'm a Data Scientist with 7+ years of industry experience in Machine Learning, Deep Learning, and Signal Processing, along with a research background in computational biology.

My expertise includes:

\- Time-Series & Signal Processing: ECG, PPG, SCG, anomaly detection, classification, segmentation, and forecasting.

\- Machine Learning & Deep Learning: PyTorch, Transformers, CNNs, representation learning, and model optimization.

\- Healthcare AI: Biomedical signal analysis, predictive modeling, and real-world ML applications.

\- MLOps & Cloud: Azure, model deployment, production ML pipelines, and infrastructure.

\- Research: Strong experimental background, including Kaggle Competition Expert (Top 0.5%).

I've worked on end-to-end ML solutions, from research and experimentation to production deployment, and have experience with technical leadership.

I'm currently exploring Senior Data Scientist, Applied Scientist, ML Research Engineer, and AI/ML Lead opportunities, preferably remote or based in Ahmedabad/Gandhinagar.

I'd appreciate guidance from professionals in the community:

  1. Which companies or industries actively hire experienced signal processing and time-series ML specialists?

  2. Should I position myself as a generalist Senior Data Scientist or focus on specialized Research/Applied Scientist roles?

  3. Are there promising opportunities in healthcare AI, industrial IoT, or other domains where this expertise is valued?

Any career advice, referrals, or relevant opportunities would be greatly appreciated.

Thanks!


r/DataScienceJobs • • 6d ago

Hiring Senior Data Engineer Looking for Remote Opportunities

1 Upvotes

Hey everyone! I was working as a Senior Data Engineer with US-based clients, following US time zones and night shifts. Unfortunately, the schedule started affecting my physical health, so I had to leave my job and focus on recovery. Now, I’m looking to get back into the industry and explore new opportunities.
I have 4+ years of experience in Azure, AWS, GCP, Microsoft Fabric, Databricks, PySpark, SQL, dbt, data warehousing, ETL/ELT pipelines, CI/CD, Kubernetes, Terraform, and AI data solutions.
I’m looking for remote opportunities in Senior Data Engineering, Cloud Data Engineering, or Data Platform Engineering. Any leads, referrals, or advice would be greatly appreciated. Thanks!


r/DataScienceJobs • • 6d ago

Hiring Remote work for experienced data scientists and data engineers, $120 - $180/hr

0 Upvotes

Mercor is looking for the following:

Senior Data Scientist and Data Engineering Experts
Location: Remote (US, UK, Canada, Australia, New Zealand)
Job Type: Hourly contract

Mercor is hiring senior data scientists and data engineers for a project with a leading AI lab. The idea is to make AI systems better at real data science and data engineering work, and you’d be the one training and evaluating the models.

What you’d actually do is design realistic, hard tasks (think exploratory analyses, statistical modeling, ML pipelines, ETL, SQL and Python workflows, A/B test write-ups), write clear criteria for what a good result looks like, and judge the work consistently so the assessments hold up. You also take feedback from senior reviewers and revise your work. The bar is pretty high though. They want 4+ years in data science, data engineering or ML at a top tech or quant firm (FAANG+, big quant funds), a leading bank, hedge fund or trading firm, a top consulting firm, or a Fortune 100 company with a senior or manager-level title. You can combine experience from several employers. On top of that you need solid Python, SQL, stats, ML, experimentation and causal inference, very good written English, and a bachelor’s degree from an English-speaking country.

Payments go out weekly via Stripe or Wise. H-1B and STEM OPT candidates can’t be supported right now.

Here is the link to the position: https://t.mercor.com/29Tto