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Data Science Sr Engineer - US Remote
Anywhere Real Estate Inc.United States, United StatesRemotefull_timeVerifiedPosted 24 Nov 2025
About the role
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.
We are proud of our award-winning culture and are consistently recognized as an employer of choice by various organizations including:
- Great Place to Work
- Forbes World's Best Employers
- Newsweek World's Most Trustworthy Companies
- Ethisphere World's Most Ethical Companies
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