Data Scientist

• Evaluate AI-built analyses on real datasets, including method choice, assumptions, and whether conclusions follow from the numbers
• Red-team statistics to expose leakage, p-hacking, confounded comparisons, and unsupported conclusions
• Write improved analyses with sound methodology, honest uncertainty, and clear takeaways
• Build, train, and evaluate machine learning models for classification, regression, clustering, and forecasting
• Apply feature engineering, cross-validation, and metric selection
• Document methodology, assumptions, and limitations for review and reproducibility
• Collaborate with engineers, product managers, and other team members
• Turn open-ended questions into well-defined analytical problems

• Professional, academic, or serious independent experience doing real data analysis in industry or research
• Proficiency in Python and its data stack (pandas, NumPy, SciPy, scikit-learn, statsmodels, or equivalents) and in SQL
• Experience working in Jupyter or similar notebook environments
• Experience with data visualization tools and libraries (matplotlib, seaborn, Plotly, or BI tools such as Tableau or Power BI)
• Working knowledge of machine learning fundamentals: model selection, overfitting, evaluation metrics, and validation strategies
• Clear written and spoken English
• No degree required
• Preferred: Background as a Data Scientist, Data Analyst, or Analytics Engineer
• Preferred: Experience reviewing, auditing, or red-teaming someone else's analysis or model output
• Preferred: Familiarity with common pitfalls in applied statistics: p-hacking, leakage, confounding, multiple comparisons
• Preferred: Familiarity with cloud platforms (AWS, GCP, or Azure), data warehouses (Snowflake, BigQuery, Redshift), and MLOps practices such as experiment tracking and model versioning
• Preferred: Experience with Git and collaborative, version-controlled workflows
• Preferred: Prior experience with AI/ML data annotation, evaluation, or model-training projects
• Self-direction and comfort working independently and asynchronously in a remote environment

• Competitive salary and performance-based bonuses
• Flexible remote work environment
• Professional growth opportunities and mentorship
• Engaging and collaborative team culture with cutting-edge projects