Anywhere

Compensation

Full 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.