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
• 35 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.

Laboratory Experience,Immunoassays,Machine Learning,Biochemistry,Assays,Research Experience,Spectroscopy,Research & Development,cGMP,Cell Culture,Molecular Biology,Data Analysis Skills

Employment Type:

Full Time

Experience:

years

Vacancy: 1