Software Engineering - Lead Data Scientist
Core
Lead Data Scientist building and running machine learning and Generative AI solutions for consumer applications, including data pipelines, model development, and production deployment.
Role type
Lead Data Scientist (ML Engineering)
Builds
Data pipelines, ML models (propensity, churn, segmentation, forecasting), and Generative AI capabilities integrated into consumer apps.
Domain
Consumer Finance / Credit Scoring / Big Data Analytics
Deliverable
production ML models
Required skills
Python (pandas, NumPy, scikit-learn, PySpark), SQL, Machine Learning (XGBoost, TensorFlow, Pytorch), AWS (SageMaker, Lambda, Bedrock), LLMs (prompt design, RAG, fine-tuning), Statistics, Experimental Design
Preferred skills
RAG workflows, vector stores, MCP server integrations, workflow orchestration (Airflow, Step Functions), regulated consumer data experience
Technologies
Python, PySpark, AWS, SageMaker, MLflow, Docker, Jupyter, XGBoost, TensorFlow, PyTorch, Bedrock, Airflow, Step Functions
Responsibilities
Build and maintain Python data pipelines for large datasets; Develop and evaluate ML models; Deploy models to production in AWS with monitoring and retraining; Design and analyze A/B tests; Lead design discussions, code reviews, and mentor team members; Integrate Generative AI capabilities using LLMs.
Seniority
Lead, hands-on IC with mentorship
