Description:
Data Scientist
Role 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.
Qualifications
Must-Have
- 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.
Preferred
- 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.