Pharma Data Scientist: ML, Big Data & AWS

RADcube - A NLogix Company; Indianapolis (IN); Hybrid; USD 110,000 - 160,000; Full time

Job summary

RADcube - A NLogix Company in Indianapolis is seeking a Data Scientist with 3–5 years of pharma-focused experience to join a DS team using Databricks and AWS. You will frame problems, build models, and analyze large datasets to drive pharma business decisions.

You will partner with business groups, engineer features, and productionize models while communicating insights to both technical and non-technical stakeholders.

Qualifications

• 3–5 years of data science / statistics / ML experience in pharma.
• Hands-on experience with Databricks for DS/ML workflows.
• Working knowledge of AWS data services.
• Strong Python and SQL; experience with ML libraries.
• Bachelor's or master's in a quantitative field.

Responsibilities

• Develop statistical and ML models on large-scale datasets in Databricks.
• Access, prepare, and engineer features from data processed via Spark and AWS services.
• Translate pharma problems into DS approaches in collaboration with business groups.
• Build and validate ETL/data pipelines to support experiments and modeling.
• Communicate results clearly to technical and non-technical stakeholders.
• Apply pharma domain knowledge to ensure models are business-relevant and interpretable.
• Collaborate with data engineers/analysts to productionize models and integrate outputs.
• Monitor model performance over time and iterate as needed.

Skills

Databricks

AWS

Big Data

PySpark

Python

SQL

Pharma domain

Communication

Education

Bachelor's degree in data science/CS

Master's degree in data science/CS

Tools

Databricks

Apache Spark

Delta Lake

Snowflake

AWS data services

Job description

RADcube - A NLogix Company in Indianapolis is seeking a Data Scientist with 3–5 years of pharma-focused experience to join a DS team using Databricks and AWS. You will frame problems, build models, and analyze large datasets to drive pharma business decisions.

You will partner with business groups, engineer features, and productionize models while communicating insights to both technical and non-technical stakeholders.