About the role
BioVid is transforming pharmaceutical market research by replacing slow, traditional methodologies with AI-augmented data systems.
In this role, you will personally analyze the data to uncover HCP prescribing behavior and behavioral insights. You will help bridge quantitative real-world data with qualitative market research, and play a key role in developing synthetic audiences (“Digital Twins”) that mirror healthcare provider prescribing behavior and patient treatment journeys, while enabling scalable forecasting, segmentation, and market intelligence solutions.
Must-Have Qualifications
Hands-on analysis of medical / pharmacy claims data (EHR preferred)
Direct, hands-on experience analyzing the data itself — not only engineering it. You can extract and predict HCP prescribing behavior for specific drugs, for specific conditions, in specific treatment areas, and tag HCP qualitative / attitudinal segments to NPIs, associating those segments with real prescribing behavior. HIPAA requirements fluent (most of our data will be deidentified)
* Analyze medical and pharmacy claims to extract and predict HCP prescribing behavior for specific drugs, conditions, and treatment areas. * Perform HCP / patient segmentation, demand forecasting, journey mapping, modeling * Help build Synthetics, simulated segments and HCP equivalents. * Machine Learning experience in modeling training and evaluating models (LLM fine tuning, training a nice to have) * Tag qualitative / attitudinal HCP segments to NPIs and link them to observed prescribing behavior. * Translate these analyses into actionable segmentation, targeting, and forecasting insights.
Data Cleaning, Processing, Augmentation and Transformation
* Data cleaning, scarcity, gap analysis, joining and data augmentation, transformation to create partitions, data marts and analytics workspaces for analysis and modeling in AWS/Athena.
Key Responsibilities
Data Integration & Modeling
* Data cleaning, scarcity, gap analysis, joining and data augmentation, transformation to create partitions, data marts and analytics workspaces for analysis and modeling inAWS/Athena. * Resolve identity matching, tokenization, and data harmonization challenges across disparate sources. * Build scalable, tested, and version-controlled data models using dbt on AWS/Athena.
Data Quality, Governance & Compliance
* Implement automated data quality checks using tools such as Great Expectations or equivalent.
Analytics, AI & Machine Learning
* Conduct advanced exploratory data analysis (EDA) and feature engineering using SQL, Python, pandas, and numpy. * Analyze claims data to model and predict HCP prescribing behavior by drug, condition, and treatment area, and associate attitudinal segments with NPIs. * Build AI-powered synthetic provider and patient personas grounded in real-world claims distributions. * Develop methods to scale qualitative research insights into national quantitative projections. * Machine Learning experience in modeling training and evaluating models. (LLM fine tuning and training a nice to have * Perform (or help perform) and automate pharmaceutical market research including: * HCP segmentation * Demand forecasting * Patient journey mapping * Audience simulation
API & Product Delivery
* Build and maintain performant backend APIs using FastAPI, deployed on AWS (e.g., ECS/Fargate, App Runner, or Lambda). * Deliver data products, personas, and insights to internal tools and client-facing applications.
Skills & Experience
* 5+ years in Analytics Engineering, Data Engineering, Data Science, or similar roles. * Proven ownership of end-to-end data pipelines and scalable analytics systems on AWS. * Hands-on experience with AWS data and analytics tooling, including Athena, S3, Glue, and SageMaker (AWS is the primary environment). * Strong experience with healthcare claims and EHR data (Rx, Dx, medical, pharmacy) and major data vendors such as IQVIA, Komodo, Symphony, or Definitive Healthcare. * Demonstrated hands-on analysis of medical/pharmacy claims to extract and predict HCP prescribing behavior and tag attitudinal segments to NPIs. * Expert SQL and strong Python skills, including pandas and large-scale data workflows. * Understanding of pharma market research, including patient journeys, HCP segmentation, and demand modeling. * Experience integrating survey or primary research data with large quantitative datasets. * Comfortable using AI coding assistants and agentic development tools to accelerate delivery.
Compensation: 120,000 +