Data Scientist

Work on challenging data science projects from end to end

Have thoughtful discussions with customers to understand their business requirements. Translate those business requirements into a data science problem.

Assess the availability of data and design a solution to solve the problem.

Train and fine-tune models, measure their performance, and deploy them in production. Measure their performance in production and make adjustments if required.

Communicate the results of the model crisply and clearly.

Building sophisticated data pipelines to process large amounts of data in Data Lakes and Data Warehouses.

Creating efficient SQL queries and understanding query execution plans for tuning queries on engines like PostgreSQL.

Performance tuning of OLAP/ OLTP databases by creating indices, tables, and views.

Strong understanding of Machine Learning and Deep Learning Concepts. (Random forests, GBMs, Deep neural nets, Convolutional NN, Recurrent NN, Ensemble methods)

Strong Python programming ability with several hands-on projects implemented.

Hands-on experience in creating models using either Tensorflow or Pytorch is required. Scikit-Learn and Pandas knowledge required.

Experience with at least one Python web framework is required. (Django, Flask, or FastAPI)

Experience in implementing a Data Science project in a real-world production environment is a big plus.

Hands-on SQL programming experience with knowledge of windowing functions, subqueries, and various types of joins.

A track record of competing in Kaggle is strongly preferred

Show us your git repo/ blog!

0-5 years of experience working on Data Science projects

Bachelors/ Masters degree in Computer Science

Multiple courses on Machine Learning and Deep Learning are required. Either as part of a degree or completed externally via self-learning

Candidates who have demonstrated a zeal for learning and keeping up to date with technology by continuing to do various courses/self-learning will be given high preference.