Lead Data Scientist
Core
Lead the design, development, validation, and operationalization of machine learning and advanced analytics solutions that power intelligent products and business capabilities.
Role type
Senior IC Lead Data Scientist (MLOps & Production)
Builds
Scalable, production-grade ML solutions for predictive, classification, recommendation, anomaly detection, forecasting, and optimization use cases.
Domain
Applied AI / Machine Learning / MLOps
Deliverable
production ML models
Required skills
Supervised and unsupervised learning, Python, scikit-learn, pandas, NumPy, XGBoost, LightGBM, PyTorch, TensorFlow, MLOps practices, CI/CD for ML, model monitoring, drift detection, feature engineering, model governance, responsible AI, SQL, batch pipelines, streaming data, API integration, observability tooling, technical mentorship
Preferred skills
Time-series forecasting, optimization, recommender systems, anomaly detection, NLP, LLM-assisted analytics, embeddings, retrieval-enhanced ML, GenAI solution patterns, feature stores, explainability frameworks, distributed training, large-scale data processing, architectural decision-making
Technologies
Azure Machine Learning, Databricks, MLflow, Azure DevOps, GitHub Actions, Docker, Kubernetes, Azure Functions, Azure Container Apps, Azure Monitor, Application Insights, Datadog, TensorBoard, TensorFlow Extended, Azure OpenAI, Azure AI Studio, Azure AI Search
Responsibilities
Lead design and deployment of ML models; translate business requirements into analytical approaches and deployment plans; build robust end-to-end ML pipelines; implement MLOps practices including experiment tracking and automated deployment; establish performance baselines and monitor production behavior; mentor data scientists and ML engineers; contribute reusable assets like feature templates and evaluation frameworks.
Seniority
Senior, hands-on IC with leadership responsibilities
