Data Scientist II
Core
Building and deploying classical machine learning models for real-world business problems like customer churn, fraud detection, demand forecasting, and recommendation systems.
Role type
Senior IC classical machine learning engineer
Builds
Production ML models for Fortune 100 brands in commerce, content, media, and sales
Domain
E-commerce, Retail, CPG, Media
Deliverable
production ML models
Required skills
Classical machine learning algorithms (Linear/Logistic Regression, Decision Trees, Random Forest, XGBoost, LightGBM, CatBoost, SVM, Naive Bayes, K-Means, DBSCAN), Feature engineering and selection, Hyperparameter optimization, Statistical modeling and diagnostics, Python (Pandas, NumPy, Scikit-learn), SQL, Spark/PySpark, Model deployment and monitoring, Model interpretability (SHAP, PDP)
Preferred skills
Mentoring junior data scientists, Cross-functional collaboration with product and engineering teams
Technologies
Python, Pandas, NumPy, Scikit-learn, XGBoost, LightGBM, CatBoost, Statsmodels, SQL, Spark, PySpark, SHAP
Responsibilities
Design, evaluate, and improve ML models using robust validation strategies; Select appropriate algorithms based on business objectives and data characteristics; Identify and address data quality issues, class imbalance, and model drift; Communicate model assumptions and results to technical and non-technical stakeholders
Seniority
Mid-Senior, hands-on IC
