Job Description

Role: Databricks Data Scientist


Location: Indianapolis, IN - onsite


Duration: 6 months

Desirable Skills:


Keyword: ~AWS| Python~


Skills: Digital : Amazon Web Service(AWS) Cloud Computing~Digital : Databricks


Experience Required: 10 & Above

Job Description:


We are seeking a Databricks Data Scientist with strong experience in Databricks Lakehouse, advanced analytics, and Genie (AI/BI) to design, build, and deploy scalable data science and AI solutions. This role will focus on transforming enterprise data into actionable insights using machine learning, natural language analytics, and self-service BI powered by Databricks Genie

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.

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