About the job
Do you know the feeling when your model’s loss is coming down, and accuracy is going up? Have you ever created a model and tested it on out-of-time samples to discover that it still provides the same accuracy? We know that feeling, we have been there, done that.
We are a startup focused on providing Data Science solutions to companies everywhere. We are building a company with a strong positive culture and a positive work environment. We value intellectual curiosity and an appetite to always keep learning. We are building a team that values these qualities.
If you are passionate about data and finding insights and always keep learning about cutting-edge algorithms and techniques, this is the right fit for you. We promise a great opportunity to work with like-minded intellectually curious people on a wide variety of data science-related problems.
If you hate the boring corporate work environment and are looking for an exciting startup work culture, we are a great fit. We relentlessly work on solving tough problems and learn a lot during the process!
What will you be doing?
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.
What we need from you
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 required. Scikit-Learn and Pandas knowledge required.
Experience with at least one Python web framework required. (Django, Flask, or FastAPI)
Experience in implementing a Data Science project in a real-world production environment a big plus.
Hands-on SQL programming experience with knowledge of windowing functions, subqueries, and various types of joins.
Track record of competing in Kaggle is strongly preferred
Show us your git repo/ blog!
Qualification
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.
