Data Scientist - Kaggle Grandmaster

Job Description

Job Description

Engagement Type: Independent Contractor
Work Mode: Fully Remote
Hours: 3040 hours/week or Full-Time (Flexible)

We are partnering with a leading AI research lab to hire a highly skilled Data Scientist with a Kaggle Grandmaster profile .

In this role, you will transform complex datasets into actionable insights, high-performing models, and scalable analytical workflows. You will collaborate closely with researchers and engineers to design rigorous experiments, build advanced statistical and machine learning models, and develop data-driven frameworks that support product and research decisions.

• Analyze large, complex datasets to uncover patterns and generate actionable insights

• Build predictive models and ML pipelines across:

  • Tabular data

  • Time-series data

  • NLP

  • Multimodal datasets

• Design and implement validation strategies, experimental frameworks, and analytical methodologies

• Develop automated data workflows, feature pipelines, and reproducible research environments

• Conduct exploratory data analysis (EDA), hypothesis testing, and model-driven investigations

• Translate analytical results into clear recommendations for engineering, product, and leadership teams

• Collaborate with ML engineers to productionize models and ensure reliable data workflows at scale

• Present findings via dashboards, structured reports, and documentation

• Kaggle Competitions Grandmaster or comparable achievement (top-tier rankings, multiple medals, or exceptional competition performance)

• 35+ years of experience in data science or applied analytics

• Strong proficiency in Python and data tools (Pandas, NumPy, Polars, scikit-learn, etc.)

• Experience building ML models end-to-end (feature engineering, training, evaluation, deployment)

• Strong understanding of statistical methods, experiment design, and causal/quasi-experimental analysis

• Familiarity with modern data stacks (SQL, distributed datasets, dashboards, experiment tracking tools)

• Excellent communication skills and ability to present analytical insights clearly

• Contributions across multiple Kaggle tracks (Notebooks, Datasets, Discussions, Code)

• Experience in AI labs, fintech, product analytics, or ML-driven organizations

• Knowledge of LLMs, embeddings, and modern ML techniques for text, image, and multimodal data

• Experience with big data ecosystems (Spark, Ray, Snowflake, BigQuery, etc.)

• Familiarity with Bayesian methods or probabilistic programming frameworks

• Work on cutting-edge AI research workflows

• Collaborate with world-class data scientists and ML engineers

• Solve high-impact, real-world data science challenges

• Experiment with advanced modeling strategies and competition-grade validation techniques

• Flexible engagement options ideal for Kaggle-level problem solvers