EG Data Scientist
Core
Apply statistical modelling and classical machine learning to validate problem framing, build baseline models, and ensure Gen AI solutions are evaluated against rigorous quantitative benchmarks.
Role type
Senior IC data scientist (statistical modelling & classical ML)
Builds
Production-ready statistical baselines and classical ML models for enterprise clients
Domain
AI services, enterprise analytics, Gen AI evaluation
Deliverable
production ML models
Required skills
statistical modelling, classical machine learning, hypothesis testing, regression, classification, clustering, time-series forecasting, causal inference basics, Python (pandas, scikit-learn, statsmodels), SQL, structured data analysis, Gen AI concepts (embeddings, RAG, prompting)
Preferred skills
time-series forecasting in production, causal inference in production, MLOps practices, regulated/Government analytics context, visualization/BI tooling (Tableau, Power BI)
Technologies
Python, SQL, MLflow, Matplotlib, Seaborn, Tableau, Power BI, AWS, Azure, GCP
Responsibilities
Translate business problems into statistical/ML problems with defined success metrics; perform exploratory data analysis to assess data quality and distributions; build and validate classical ML models as baselines or standalone solutions; apply rigorous statistical validation (train/test/holdout, cross-validation, significance testing); partner with AI Engineers on evaluation design for Gen AI solutions; monitor model performance and data drift for production classical models; advise stakeholders on when classical approaches are more defensible than Gen AI.
Seniority
Senior, hands-on IC
