Senior Data Scientist

Get AI-powered advice on this job and more exclusive features. This range is provided by People In AI. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. 00/yrDirect message the job poster from People In AIPlacing the Top AI and Machine Learning TalentSenior Data Scientist (Ranking & Recommendation Systems)Remote (US Only)$160,000 – $175,000 Base + BonusEligibility: U. S.

Citizens or Green Card Holders OnlyWe’re looking for a sharp, pragmatic Senior Data Scientist to join a high-impact team focused on ranking, retrieval, and intelligent prioritization systems. This is a modeling-forward role for someone who thrives on solving real-world problems using clean code, principled experimentation, and scalable ML infrastructure.

Build the Core Intelligence Behind Decision SystemsDesign models that retrieve and rank high-value entities under noisy, ambiguous conditions. Apply techniques from recommender systems, representation learning, and constrained optimization to drive measurable outcomes. Collaborate cross-functionally to translate product intuition and messy data into well-defined modeling problems.

Technical Team, Product-Minded CultureWork with a team of applied scientists, engineers, and product leaders who bring deep experience in ML infrastructure and system design. Emphasis on upstream modeling — the work starts well before model selection and continues through post-deployment iteration. Contribute to an environment that values curiosity, rigor, and getting things done without excess process. Remote-First with Room to GrowU.

-based remote role with flexibility and focus. Minimal bureaucracy, lean processes, and full autonomy to drive your work forward. Opportunities for advancement, technical ownership, and mentorship as the team scales. What the Role InvolvesBuild and iterate on models for retrieval, ranking, and personalization using collaborative filtering, embeddings, and optimization-based approaches. Evaluate model quality through MAP, NDCG, Recall@K, and other offline metrics.

Partner with engineers to deploy models into production and monitor their performance. Write clear, reproducible research and run offline experiments to support ongoing improvements. Help define and improve best practices for experimentation, testing, and code quality. What We’re Looking For3+ years of experience in data science, ML engineering, or applied modeling roles. Experience with ranking or recommendation systems, ideally in production environments.

Proficiency in Python and modern ML libraries such as PyTorch, TensorFlow, Scikit-learn, or XGBoost. Strong statistical intuition, hands-on coding skills, and an understanding of model evaluation. Comfortable working independently, taking ownership of end-to-end modeling tasks. Bonus: background in optimization, information retrieval, or experimentation infrastructure. Must be a U. S. Citizen or Green Card holder.

This is a rare opportunity to work on technically rich problems with immediate real-world impact — in a fast-moving team that values clear thinking, clean modeling, and production-grade execution. If you're excited about building intelligent ranking systems from the ground up, we’d love to hear from you.

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