Data Scientist, AI/ML Model Quality
Core
Build and maintain intelligent systems, validation frameworks, and monitoring pipelines to ensure the integrity of data powering ML and GenAI models for Wallet, Payments, and Commerce.
Role type
Senior IC data scientist (ML/GenAI model quality)
Builds
Validation frameworks, observability metrics, telemetry analysis pipelines, and dashboards for ML/GenAI health
Domain
Financial services (Wallet, Payments, Commerce) + Machine Learning / Generative AI
Deliverable
production ML models
Required skills
statistical methods, data drift detection, bias and fairness analysis, Python, SQL, distributed computing, ML observability, GenAI telemetry analysis
Preferred skills
data visualization, LLM evaluation frameworks, Bayesian/causal graph approaches, uncertainty quantification, ML monitoring platforms, regulatory compliance knowledge
Technologies
Python, Pandas, NumPy, Scikit-learn, SQL, PySpark, Spark, Tableau, Apache Superset, Databricks, LangSmith, MLflow, Weights & Biases
Responsibilities
Curate and maintain gold-standard ground-truth datasets for model evaluation; audit training data for bias and fairness; define and track data quality metrics; design automated data quality rules for CI/CD workflows; define ML observability metrics and analyze telemetry; design dashboards for real-time model health views; identify degradation patterns in GenAI systems
Seniority
Senior, hands-on IC
