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Data Science Associate Jobs in Philadelphia, PA (NOW HIRING)

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Data Science Associate information

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$58K

$68.7K

$130.2K

How much do data science associate jobs pay per year?

As of Aug 7, 2026, the average yearly pay for data science associate in Philadelphia, PA is $68,657.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $60,000.00 per year, depending on experience, location, and employer.

How does a data science associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

What can I do with a data science associate?

A data science associate typically supports data analysis, data cleaning, and model development using tools like Python, R, or SQL. They may assist in preparing reports, visualizations, and insights for decision-making, often working under the guidance of senior data scientists or analysts.

What is a data science associate?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What are the key skills and qualifications needed to thrive as a data science associate?

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

What is the difference between Data Science Associate vs Data Analyst?

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What are the most commonly searched types of Data Science jobs in Philadelphia, PA? The most popular types of Data Science jobs in Philadelphia, PA are:
What are popular job titles related to Data Science Associate jobs in Philadelphia, PA? For Data Science Associate jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Data Science Associate jobs in Philadelphia, PA look for? The top searched job categories for Data Science Associate jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Data Science Associate jobs? Cities near Philadelphia, PA with the most Data Science Associate job openings:
Data Science Associate jobs near you
Infographic showing various Data Science Associate job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $68,657 per year, or $33 per hour.

Healthcare Data Scientist & AI Solutions

BioVid

Bristol, PA • On-site

$120K/yr

Full-time

Re-posted 17 days ago

Job description

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.

Apply