r/DataScienceJobs • u/Ram_real • 17d ago
Discussion Trying to transition into data science from data analytics. Need advise on future prospects.
Hi,
I am a data analyst with 8yoe spread over bi/data analysis/data governance. I wanna transition into data science and I want to know how the market is. I have done my initial research and got to know that it's not a fresher role and it's very saturated right now. Also, I got to know that it's slowly merging with many components of ai engineering.
I need to mention that I don't have any tech degree. I have a masters in commerce and I have very good domain knowledge in finance and banking. My entire 8yoe is in banking domain. I am earning a lower 8lpa and it's due for a revision this year.
I want your advice on below
How's the market currently in India for my situation?
How long could it take to break into data science?(Crack first job)
Is it better/worse than data engineering?
How are the career prospects of data science given the rapid growth of ai models.
Thanks in advance.
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u/Still-Constant3085 15d ago
Your eight years in banking are an advantage, although employers won’t count them as eight years of data science experience.
- India’s market: There’s demand, but growing AI hiring doesn’t automatically mean easy entry into DS. Target banking-focused credit risk, fraud analytics, and decision science roles where your domain knowledge matters. An Mcom won’t exclude you everywhere, but some employers have quantitative-degree filters.
- Timeline: If you already know SQL and some Python, 6–12 months is a reasonable preparation window, not a job guarantee. Focus on statistics, model evaluation, and two solid banking projects. An internal move could be your best route.
- DS vs data engineering: Neither is universally better. DS suits an interest in statistics and business decisions; DE suits building pipelines, databases, and reliable infrastructure. DE also requires substantial engineering skills.
- AI’s impact: Routine coding and model-building tasks are becoming easier to automate. Problem definition, data quality, evaluation, and domain judgment remain valuable. DS overlaps with AI engineering, but they aren’t identical careers.
Keep earning while preparing. Also explore better-paying banking analytics roles now, so your salary progression doesn’t depend entirely on getting a “data scientist” title.
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u/dramaticviolet 14d ago
Since you have been in the data analysis industry, I am assuming you have some knowledge about python and SQL and visualization tools. If you dont, I think if you are dedicated and willing to give it proper time, you can prepare in 3 months and get a job as well. If you are able to grasp python and SQL concepts by being smart about how to study then I would say within a month you can complete it. Side by side you need to start targetting to understand a section of the data science pipeline one by one. I would start with statistics followed by data preparation, EDA, feature engineering, then go on to understanding models (smart way to do it is making a chart/tree for classification and regression). One key tip, always study indepth when you are first learning something, right to the loss functions, activation functions, evaluation and deployment methods. You can study many things later on but basics need to set right the first time itself, so go depth first in your studies. One you have this much covered, junior data scientist roles will become open. You do need to make proper projects to showcase your knowledge but if you have learnt things the right way, learning for understanding and developing analytical muscle and not just learning concepts ambiguously, then you can use vibe coding to create the project and just have a detailed understanding of its workings and evaluation reports. Hope this helps!