Pharma Data Scientist - ML on Databricks (Hybrid)

Socket.dev; Indianapolis (IN); Hybrid; USD 110,000 - 170,000; Full time

Job summary

Socket.dev is seeking a Data Scientist with 3-5 years of experience in the pharma industry to join a pharma-focused data team in a hybrid role based in Indianapolis, IN. You will blend statistical modeling with data engineering fluency, leveraging Databricks and AWS to build models and analyses that drive pharma business decisions.

You will partner with business groups to frame problems, create robust data pipelines, and communicate results to both technical and non-technical stakeholders.

Qualifications

• 3-5 years of data science/ML experience in pharma
• Hands-on Databricks for ML workflows
• Experience with AWS data services
• Strong Python and SQL skills with ML libraries
• Ability to translate pharma problems into DS approaches
• Strong communication with business stakeholders
• Bachelor's or master's degree in a quantitative field

Responsibilities

• Develop statistical and ML models using large datasets in Databricks
• Access, engineer features from Spark and AWS data services
• Collaborate with business groups to frame pharma problems for DS solutions
• Build and validate ETL/data pipelines to support modeling workflows
• Communicate results to technical and non-technical stakeholders
• Apply pharma domain knowledge to ensure model relevance
• Work with data engineers to productionize models and integrate outputs
• Monitor model performance and iterate over time

Skills

Data science

PySpark

Python

SQL

AWS

ML

Statistics

Big Data

Communication

Education

Bachelor's or Master's in Data Science / Statistics / CS

Tools

Databricks

Spark / PySpark

Delta Lake

Snowflake

Job description

Socket.dev is seeking a Data Scientist with 3-5 years of experience in the pharma industry to join a pharma-focused data team in a hybrid role based in Indianapolis, IN. You will blend statistical modeling with data engineering fluency, leveraging Databricks and AWS to build models and analyses that drive pharma business decisions.

You will partner with business groups to frame problems, create robust data pipelines, and communicate results to both technical and non-technical stakeholders.