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, Large Language Models (LLMs), Generative AI (GenAI))
- 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
- 1 to 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.
