The Role
Develop statistical and machine learning models using large-scale pharma datasets in Databricks, AWS, Spark, Python, and SQL. Engineer features, build ETL pipelines, validate and monitor models, and collaborate with data engineers and analysts to productionize outputs. Partner with pharma business groups to frame analytical problems and communicate insights and recommendations to technical and non-technical stakeholders.
Summary Generated by Built In
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
Skills Required
- 3-5 years of data science, applied statistics, or machine learning experience specifically within the pharmaceutical industry
- Hands-on experience with Databricks for data science and machine learning workflows
- Working knowledge of AWS data services
- Strong experience with big data processing using Apache Spark and PySpark
- Experience building ETL pipelines to support data science workflows
- Strong Python and SQL skills, including experience with machine learning libraries
- Ability to understand pharmaceutical business needs and communicate with pharma business groups
- Strong communication skills and 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
- Experience with Delta Lake, Snowflake, or similar modern data platforms
- Familiarity with MLOps practices and model deployment and monitoring
- Experience supporting pharma commercial, clinical, or R&D data science functions
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The Company
What We Do
RADcube is a technology consulting and software development firm founded in 2015 and headquartered in Carmel, Indiana. It helps organizations turn enterprise ideas into practical innovations through digital transformation, custom software, data analytics, artificial intelligence, cloud computing, cybersecurity, and intelligent automation. The company serves healthcare, finance, government, and manufacturing clients, combining human-centric delivery with responsible, accountable technology solutions designed to produce measurable business outcomes.
