Healthcare Data Scientist & AI Solutions

BioVid

$90K — $130K *
Healthcare
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in analytics, engineering, or data science roles
  • Proven experience with AWS data services (Athena, S3, Glue, SageMaker)
  • Extensive knowledge of healthcare claims and EHR data
  • Strong analytical skills in predicting HCP prescribing behavior
  • Expertise in SQL and proficiency in Python for data workflows
  • Familiarity with pharma market research and patient journeys
  • Comfortable using AI tools for coding assistance.

Responsibilities

  • Analyze medical and pharmacy claims data to predict HCP prescribing behavior
  • Perform segmentation, demand forecasting, and journey mapping
  • Build and maintain scalable data models using dbt on AWS/Athena
  • Implement automated data quality checks for compliance and governance
  • Conduct exploratory data analysis and feature engineering with SQL and Python
  • Develop AI-powered synthetic personas based on claims distributions
  • Deliver actionable insights through APIs and internal tools.

Benefits

  • Opportunities for professional growth in a cutting-edge field
  • Collaborative work environment with a focus on innovation
  • Access to advanced analytics tools and technologies
  • Engagement in meaningful projects impacting healthcare decisions
  • Flexibility in work arrangements to promote work-life balance.
Full Job Description
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.

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