Data Scientist

at Product Engineering MNC (FinTech Domain)

Agency job
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Bengaluru (Bangalore)
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5 - 10 yrs
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₹10L - ₹40L / yr
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Full time
Skills
Data Science
Data Scientist
Python
Statistical Modeling
Statistical Analysis
Artificial Intelligence (AI)
Machine Learning (ML)

Role : Sr Data Scientist / Tech Lead – Data Science

Number of positions : 8

Responsibilities

  • Lead a team of data scientists, machine learning engineers and big data specialists
  • Be the main point of contact for the customers
  • Lead data mining and collection procedures
  • Ensure data quality and integrity
  • Interpret and analyze data problems
  • Conceive, plan and prioritize data projects
  • Build analytic systems and predictive models
  • Test performance of data-driven products
  • Visualize data and create reports
  • Experiment with new models and techniques
  • Align data projects with organizational goals

Requirements (please read carefully)

  • Very strong in statistics fundamentals. Not all data is Big Data. The candidate should be able to derive statistical insights from very few data points if required, using traditional statistical methods.
  • Msc-Statistics/ Phd.Statistics
  • Education – no bar, but preferably from a Statistics academic background (eg MSc-Stats, MSc-Econometrics etc), given the first point
  • Strong expertise in Python (any other statistical languages/tools like R, SAS, SPSS etc are just optional, but Python is absolutely essential). If the person is very strong in Python, but has almost nil knowledge in the other statistical tools, he/she will still be considered a good candidate for this role.
  • Proven experience as a Data Scientist or similar role, for about 7-8 years
  • Solid understanding of machine learning and AI concepts, especially wrt choice of apt candidate algorithms for a use case, and model evaluation.
  • Good expertise in writing SQL queries (should not be dependent upon anyone else for pulling in data, joining them, data wrangling etc)
  • Knowledge of data management and visualization techniques --- more from a Data Science perspective.
  • Should be able to grasp business problems, ask the right questions to better understand the problem breadthwise /depthwise, design apt solutions, and explain that to the business stakeholders.
  • Again, the last point above is extremely important --- should be able to identify solutions that can be explained to stakeholders, and furthermore, be able to present them in simple, direct language.

 http://www.altimetrik.com

https://www.youtube.com/watch?v=3nUs4YxppNE&;feature=emb_rel_end">https://www.youtube.com/watch?v=3nUs4YxppNE&;feature=emb_rel_end

https://www.youtube.com/watch?v=e40r6kJdC8c

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