Job Opportunities API

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.