Machine Learning Data Scientist

About This Role

Analyze large and complex datasets to build predictive models, statistical analyses, and machine learning pipelines, ultimately contributing to the productionization of models in collaboration with ML engineers.

Responsibilities

• Analyze large, complex datasets to uncover patterns and inform modeling direction
• Build predictive models, statistical analyses, and machine learning pipelines across various data types
• Design and implement robust validation strategies and analytical methodologies
• Develop automated data workflows and reproducible research environments
• Conduct exploratory data analysis and model-driven investigations to support teams
• Collaborate with ML engineers to productionize models and ensure reliable data workflows

Requirements

• Kaggle Competitions Grandmaster or comparable achievement
• 3–5+ years of experience in data science or applied analytics
• Strong proficiency in Python and data tools (Pandas, NumPy, Polars, scikit-learn)
• Experience building ML models end-to-end
• Solid understanding of statistical methods and experiment design
• Familiarity with modern data stacks: SQL, distributed datasets, dashboards, and experiment tracking tools
• Excellent communication skills

Qualifications

• 3-5+ years of experience in data science or applied analytics

Nice to Have

• Strong contributions across multiple Kaggle tracks
• Experience in an AI lab, fintech, product analytics, or ML-focused organization
• Knowledge of LLMs, embeddings, and modern ML techniques
• Experience with big data ecosystems (Spark, Ray, Snowflake, BigQuery)
• Familiarity with statistical modeling frameworks such as Bayesian methods

Skills

* Required skills