Data Scientist (Kaggle-Grandmaster)

Role DescriptionMercor is hiring on behalf of a leading AI research lab to bring on 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 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.

What You’ll DoAnalyze large, complex datasets to uncover patterns, develop insights, and inform modeling directionBuild predictive models, statistical analyses, and machine learning pipelines across tabular, time-series, NLP, or multimodal dataDesign and implement robust validation strategies, experiment frameworks, and analytical methodologiesDevelop automated data workflows, feature pipelines, and reproducible research environmentsConduct exploratory data analysis (EDA), hypothesis testing, and model-driven investigations to support research and product teamsTranslate modeling outcomes into clear recommendations for engineering, product, and leadership teamsCollaborate with ML engineers to productionize models and ensure data workflows operate reliably at scalePresent findings through well-structured dashboards, reports, and documentation



QualificationsKaggle Competitions Grandmaster or comparable achievement: top-tier rankings, multiple medals, or exceptional competition performance3–5+ years of experience in data science or applied analyticsStrong proficiency in Python and data tools (Pandas, NumPy, Polars, scikit-learn, etc. )Experience building ML models end-to-end: feature engineering, training, evaluation, and deploymentSolid understanding of statistical methods, experiment design, and causal or quasi-experimental analysisFamiliarity with modern data stacks: SQL, distributed datasets, dashboards, and experiment tracking toolsExcellent communication skills with the ability to clearly present analytical insightsNice to HaveStrong contributions across multiple Kaggle tracks (Notebooks, Datasets, Discussions, Code)Experience in an AI lab, fintech, product analytics, or ML-focused organizationKnowledge of LLMs, embeddings, and modern ML techniques for text, images, and multimodal dataExperience working with big data eco

Systems (Spark, Ray, Snowflake, BigQuery, etc. )Familiarity with statistical modeling frameworks such as Bayesian methods or probabilistic programmingWhy JoinGain 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.