Job Description
Summary of Role: Work back from the business problems to be solved, collect proper data to do statistical analysis, select proper machine learning and/or deep learning modeling approaches, eventually rollout ML models in production environment to perfect business decision. Meanwhile, coach junior associates during project collaborations. Responsibilities: • Understand business needs and explore appropriate data sources - be curious and proactive in exploring and understanding data. • Perform data aggreagation, and feature engineering needed; write Python programming code to make visualizations, build, validate, and implement models. • Collaborate with other data scientists and engineers. • Be flexible and open to innovative ideas and alternative ways of solving problems. • Be able to clearly communicate with and present the results to non-tech partners. Experience: • Master's degree (or higher) in Statistics, Data Science, Mathematics, Economics or related analytical discipline. • At least one years’ experience in building end-to-end models in python (or similar language) through production. This requirement can be omitted for Ph.D. degree holders. Skills: • Proficiency in SQL and Python programming languages (pandas, numpy, scipy, scikit-learn, etc.) • In-depth understanding of statistical knowledge and machine learning algorithms. Exposure and some deep learning knowledge are required. • Specifically, expertise with the following techniques are must-haves to perform daily work: Linear Regression and GLM, GBM, Random Forest, XGboost, segmentation techniques, etc. Knowledge on Large Lanuage Models and Neural Networks are nice to have. • Effective communication skills. • Ability to learn new skills and independently take on tasks. Apply tot his job
Ready to Apply?
Don't miss out on this amazing opportunity!
🚀
Apply Now