Data Scientist; Kaggle-Grandmaster

Data Scientist

Role Description

Mercor is hiring on behalf of a leading AI research lab to bring on a highly skilled Data Scientist with a Kaggle Grand master profile
. In this role, you will transform complex datasets into actionable insights, high-performing models, and scalable analytical workflows. You will work closely with researchers and engineers to design rigorous experiments, build advanced statistical and ML models, and develop data-driven frameworks to support product and research decisions.

• Analyze large, complex datasets to uncover patterns, develop insights, and inform modeling direction
• Build predictive models, statistical analyses, and machine learning pipelines across tabular, time-series, NLP, or multimodal data
• Design and implement robust validation strategies, experiment 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 to support research and product teams
• Translate modeling outcomes into clear recommendations for engineering, product, and leadership teams
• Collaborate with ML engineers to product ionize models and ensure data workflows operate reliably at scale
• Present findings through well-structured dashboards, reports, and documentation

• Kaggle Competitions Grand master or comparable achievement: top-tier rankings, multiple medals, or exceptional competition performance
• 3–5+ years of experience in data science or applied analytics
• Strong proficiency in Python and data tools (Pandas, Num Py, Polars, scikit-learn, etc.)
• Experience building ML models end-to-end: feature engineering, training, evaluation, and deployment
• Solid understanding of statistical methods, experiment design, and causal or quasi-experimental analysis
• Familiarity with modern data stacks: SQL, distributed datasets, dashboards, and experiment tracking tools
• Excellent communication skills with the ability to clearly present analytical insights

• Strong contributions across multiple Kaggle tracks (Notebooks, Datasets, Discussions, Code)
• Experience in an AI lab, fintech, product analytics, or ML-focused organization
• Knowledge of LLMs, embeddings, and modern ML techniques for text, images, and multimodal data
• Experience working with big data ecosystems (Spark, Ray, Snowflake, Big Query, etc.)
• Familiarity with statistical modeling frameworks such as Bayesian methods or probabilistic programming

• Gain exposure to cutting‑edge AI research workflows, collaborating closely with data scientists, ML engineers, and research leaders shaping next‑generation analytical systems.
• Work on high‑impact data science challenges while experimenting with advanced modeling strategies, new analytical methods, and competition‑grade validation techniques.
• Collaborate with world‑class AI labs and technical teams operating at the frontier of forecasting, experimentation, tabular ML, and multimodal analytics.
• Flexible engagement options (30–40 hrs/week or full‑time) — ideal for data scientists eager to apply Kaggle‑level problem‑solving to real‑world, production analytics.
• Fully remote and globally flexible work structure — optimized for deep analytical work, async collaboration, and high‑output research.

Not Applicable

Full-time

Engineering and Information Technology

Software Development

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Location:

London, England, United Kingdom