Build and improve inventory demand forecasting models using ML and statistical methods.
Own ML models end-to-end: data collection → feature engineering → training → deployment → monitoring → iteration.
Develop decision systems that support inventory planning, pricing, and demand decisions.
Build and maintain data pipelines and API integrations for external and internal data sources.
Work with messy real-world data to ensure model reliability through rigorous validation and testing.
Implement LLM/AI-agent workflows to translate domain logic into automated processes.
Operate independently in a small team, setting priorities, unblocking challenges, and communicating tradeoffs clearly.

Requirements

5+ years of Python experience in production ML systems (beyond notebooks/research).
Deep experience with statistical modeling, including ensemble methods, kNN, calibration, cross-validation, and feature engineering.
Expertise in time-series modeling & forecasting, including seasonality, trend decomposition, safety stock, and demand planning.
Proven track record of shipping ML models that drive real business decisions (forecasting, pricing, demand planning).
Strong intuition for messy, real-world data, including bias correction, stale signal handling, error cancellation, and distribution shifts.
Experience with API integration and data pipeline architecture at scale.
Hands-on experience with LLM/AI-agent workflows, including prompt engineering and evaluation frameworks.
Proven ability to validate models rigorously: LOO, backtesting, production vs offline metric gaps.
Self-directed, comfortable in a fast-evolving, small team environment.

Benefits

Remote Work: Work from anywhere—our team is global, and we value work-life balance.
Growth Opportunities: As a key player i you’ll have the chance to shape your role and grow with us.
Innovative Culture: Join a team that is passionate about leveraging data to solve challenges and drive success in a rapidly evolving market.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Pythonmachine learningstatistical modelingensemble methodskNNcalibrationcross-validationfeature engineeringtime-series modelingforecasting

Soft Skills

self-directedcommunicationprioritizationproblem-solvingteam collaboration