Data Scientist - Kaggle Grandmaster

Engagement Type: Independent Contractor

Work Mode: Fully Remote

Hours: 30-40 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 Grand master 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 product ionize models and ensure reliable data workflows at scale
• Present findings via dashboards, structured 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, 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, Big Query, 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

YO IT Consulting