Description

Key Responsibilities

Data Science & Machine Learning · Design, develop, and deploy machine learning models using Databricks (MLflow, Spark ML, Python). · Implement end-to-end ML pipelines (data ingestion → training → deployment → monitoring). · Collaborate with data engineers to ensure reliable, high-quality datasets in the Lakehouse. Databricks & Lakehouse Architecture · Leverage Databricks Lakehouse (Delta Lake, Unity Catalog) for scalable analytics. · Optimize Spark jobs for performance and cost efficiency. · Apply best practices for data governance, lineage, and security. Genie (AI/BI & Natural Language Analytics) · Configure and enable Databricks Genie for self-service analytics. · Design semantic layers and curated datasets optimized for natural language queries. · Partner with business stakeholders to translate questions into Genie-enabled insights. Business Enablement & Collaboration · Work closely with product owners, analysts, and business leaders to identify high-value use cases. · Communicate complex analytical results in a clear, business-friendly manner. Required Qualifications · Bachelor’s or master’s degree in data science, Computer Science, Statistics, Engineering, or a related field. · 4+ years of experience in data science or advanced analytics. · Hands-on experience with Databricks and Apache Spark. · Strong programming skills in Python (PySpark, Pandas, NumPy, Scikit-learn). · Experience building and deploying ML models in production. · Solid understanding of SQL and data modeling. · Experience with MLflow, model lifecycle management, and experimentation

Key Skills

Education

Bachelor's or Master's degrees