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