Data Scientist

Mercor; Remote; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

A leading AI research lab is looking for a Data Scientist to transform complex datasets into actionable insights. Ideal candidates should have a Kaggle Grandmaster profile and 3+ years of experience in data science. Responsibilities include analyzing large datasets, building predictive models, and collaborating with engineering teams. The position offers fully remote working conditions and flexible hours for those eager to apply advanced analytical skills to real-world challenges.

Leistungen

Flexible engagement options (30-40 hrs / week or full-time)

Fully remote and globally flexible work structure

Exposure to cutting-edge AI research workflows

Qualifikationen

• Kaggle Grandmaster or comparable achievement in competitions.
• 3+ years of experience in data science or applied analytics.
• Strong proficiency in Python and relevant data analysis tools.

Aufgaben

• Analyze large datasets to uncover patterns and develop insights.
• Build predictive models and machine learning pipelines.
• Collaborate with ML engineers to ensure model reliability.

Kenntnisse

Python

Data tools (Pandas, NumPy, Polars, scikit-learn)

Machine Learning

Statistical analysis

SQL

Bayesian methods

Jobbeschreibung

Role Description

Mercor 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 Do

• 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 productionize models and ensure data workflows operate reliably at scale
• Present findings through well-structured dashboards, reports and documentation

Qualifications

• 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 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

Nice to Have

• 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, BigQuery, etc.)
• Familiarity with statistical modeling frameworks such as Bayesian methods or probabilistic programming

Why Join

• 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.

Key Skills

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