Data Scientist

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

Data Scientist

Hybrid – Indianapolis, IN

About the Role

We are seeking a Data Scientist with 3-5 years of experience working specifically within the pharma industry to join a pharma-focused data team. This role combines applied statistical/ML modeling with strong data engineering fluency, working against large-scale data housed in Databricks and AWS. You will partner with business groups to frame problems, build models and analyses that answer them, and communicate results in terms that drive pharma business decisions.

Key Responsibilities

• Develop statistical models, machine learning models, and advanced analyses using large-scale datasets in Databricks
• Access, prepare, and engineer features from data processed through Apache Spark and AWS data services
• Partner with business groups to understand pharma-specific problems and translate them into data science approaches
• Build and validate ETL/data pipelines as needed to support modeling and experimentation workflows
• Communicate modeling results, insights, and recommendations clearly to both technical and non-technical business stakeholders
• Apply pharma domain knowledge to ensure models and analyses are relevant and interpretable in a business context
• Collaborate with data engineers and analysts to productionize models and integrate outputs into reporting/decision workflows
• Monitor model performance over time and iterate as needed

Requirements

Required Qualifications

• 3-5 years of data science / applied statistics / machine learning experience specifically within the pharma industry
• Hands‑on experience with Databricks for data science/ML workflows
• Working knowledge of AWS data services
• Strong experience with Big Data processing using Apache Spark, PySpark.
• Experience building ETL pipelines to support data science workflows
• Strong Python and SQL skills; experience with ML libraries
• Demonstrated ability to understand pharma business needs and speak to pharma business groups
• Strong communication skills with demonstrated ability to present technical findings to business stakeholders
• Bachelor's or master's degree in data science, Statistics, Computer Science, or a related quantitative field

Preferred Qualifications

• Experience with Delta Lake, Snowflake, or similar modern data platforms
• Familiarity with MLOps practices and model deployment/monitoring
• Prior experience supporting pharma commercial, clinical, or R&D data science functions