1

Data Science Pharma Jobs (NOW HIRING)

Lead complex data science initiatives across audience decisioning, marketing decision science, pharma direct measurement, and employer direct analytics, driving measurable business impact. * Derive ...

Data Scientist

Indianapolis, IN · On-site

$110 - $170/hr

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 ...

Posted today

Director, Data Science

Boston, MA · On-site

$235K - $307K/yr

About Formation Bio Formation Bio is a tech and AI driven pharma company differentiated by ... About the Position As the Director of Data Science at Formation Bio, you will be at the forefront ...

Minimum of 3 plus years of relevant knowledge using data science and/or analytical techniques to ... Pharma Data Assets:Knowledge in mining medical claims/EMR, social media, etc. data with a strategic ...

New

Minimum of 3 plus years of relevant knowledge using data science and/or analytical techniques to ... Pharma Data Assets:Knowledge in mining medical claims/EMR, social media, etc. data with a strategic ...

New

... science, data strategy, and data solutions.The preferred candidate should have intellectual ... Pharma Data Assets:-Knowledge in mining medical claims/EMR, social media, etc. data with a ...

New

About the Position As the Director of Data Science at Formation Bio, you will be at the forefront ... sciences (biotech, pharma, consulting) * Strong programming skills, particularly in Python

AWS Data Engineer

Alameda, CA · On-site

$129K - $155K/yr

AWS Data Engineer Work Location: Alameda CA Duration: Contract to hire or FTE Experience: 10 to max ... Life Science Pharma & Commercial Operations Domain Knowledge is must Expierence Range 8-12 Years ...

Data Science Associate

Chantilly, VA · On-site

$65K - $68K/yr

... pharma company in the US!With our sites in Chantilly and Manassas, Virginia, we have R&D through ... Master's Degree in Data Science, Analytics, Statistics, Computer Science, or a related quantitative ...

New

Provide statistical expertise and develop data science solutions to Pharma technical operations, including process development, analytical method development, commercial manufacturing and quality ...

next page

Showing results 1-20

Data Science Pharma information

See salary details

$37.5K

$122.7K

$196.5K

How much do data science pharma jobs pay per year?

As of Aug 10, 2026, the average yearly pay for data science pharma in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is data science in the pharmaceutical industry?

Data science in the pharmaceutical industry involves using advanced analytics, machine learning, and statistical methods to analyze complex data sets related to drug discovery, clinical trials, and patient outcomes. Data scientists in pharma help accelerate drug development, optimize clinical study designs, and identify new therapeutic targets by extracting meaningful insights from large volumes of biological and medical data. Their work improves decision-making, reduces costs, and ultimately leads to more effective treatments for patients.

What does a data science pharma do?

A data science professional in the pharmaceutical industry analyzes large datasets to identify patterns, support drug development, and improve patient outcomes. They use statistical methods, machine learning, and data visualization tools to inform decision-making and optimize research processes.

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

AspectData Science PharmaData Analyst Pharma
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; knowledge of programming languages like Python or RBachelor's in Statistics, Mathematics, or related fields; proficiency in Excel, SQL, and basic analytics tools
Work EnvironmentDeveloping predictive models, machine learning, advanced analytics in pharmaceutical R&D and marketingData reporting, visualization, and basic analysis to support decision-making in pharma companies
Employer & Industry UsagePharmaceutical companies, biotech firms, healthcare analytics providersPharmaceutical companies, healthcare organizations, research institutions

Data Science Pharma professionals focus on advanced analytics, machine learning, and predictive modeling to drive innovation in pharma. Data Analysts Pharma handle data reporting and basic analysis to support operational decisions. Both roles are essential but differ in complexity and technical requirements.

How does a data scientist in the pharmaceutical industry typically collaborate with cross-functional teams during drug development projects?

Data scientists in pharma regularly work alongside clinical researchers, biostatisticians, regulatory specialists, and product managers to analyze complex datasets from clinical trials and real-world evidence. They translate data-driven insights into actionable recommendations that guide decision-making throughout the drug development pipeline. Effective communication and teamwork are essential, as data scientists must both understand scientific objectives and explain analytical findings to colleagues from diverse backgrounds. This collaborative environment fosters innovation and ensures that data-driven approaches contribute meaningfully to advancing new therapies.

Do pharmacy companies hire data scientists?

Yes, pharmacy companies often hire data scientists to analyze clinical data, optimize drug development, and improve patient outcomes. These roles typically require skills in statistical analysis, machine learning, and programming tools like Python or R, and may involve working with large healthcare datasets in a regulated environment.

What are the key skills and qualifications needed to thrive as a data scientist in the pharmaceutical industry, and why are they important?

To thrive as a Data Scientist in pharma, you need a strong background in statistics, machine learning, and domain knowledge in biology or chemistry, usually backed by an advanced degree in a quantitative field. Familiarity with tools like Python, R, SQL, and experience with clinical trial data systems or bioinformatics platforms is commonly required. Strong analytical thinking, collaboration, and the ability to communicate complex data insights to multidisciplinary teams are vital soft skills. These capabilities are crucial for extracting meaningful insights from complex biomedical data, supporting evidence-based decision-making, and driving innovation in drug development.
More about Data Science Pharma jobs
What cities are hiring for Data Science Pharma jobs? Cities with the most Data Science Pharma job openings:
What states have the most Data Science Pharma jobs? States with the most job openings for Data Science Pharma jobs include:
Infographic showing various Data Science Pharma job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Job description

GoodRx is the leading prescription savings platform in the U.S. Trusted by more than 25 million consumers and 750,000 healthcare professionals annually, GoodRx provides access to savings and affordability options for generic and brand-name medications at more than 70,000 pharmacies nationwide, as well as comprehensive healthcare research and information. Since 2011, GoodRx has helped consumers save nearly $75 billion on the cost of their prescriptions.
Our goal is to help Americans find convenient and affordable healthcare. We offer solutions for consumers, employers, health plans, and anyone else who shares our desire to provide affordable prescriptions to all Americans.
How We Work with AI
AI is a core part of how we operate, and as a Lead Data Scientist you are expected to help shape how AI is applied responsibly across data science and machine learning workflows.
  • You evaluate emerging AI and machine learning technologies pragmatically, balancing business value, model quality, operational complexity, and responsible use.
  • You identify opportunities to leverage generative AI and advanced machine learning techniques to improve modeling, experimentation, decision-making, and team productivity while ensuring solutions remain reliable, explainable, and maintainable.
  • You help establish and evolve best practices for responsible AI development, model governance, and reproducibility across the organization.

What You'll Do
You will partner closely with data scientists, engineers, product managers, and business stakeholders to design, build, and deploy models that shape how GoodRx reaches its consumers and serves its partners. Day to day responsibilities include, but are not limited to:
  • Lead complex data science initiatives across audience decisioning, marketing decision science, pharma direct measurement, and employer direct analytics, driving measurable business impact.
  • Derive insights from large, complex datasets to deepen our understanding of user identity and the customer journey from online discovery to in-store retail, connecting fragmented signals into a coherent view of how users move through the GoodRx ecosystem.
  • Build audience selection, segmentation, propensity, and lookalike models that ensure the right message reaches the right user at the right moment across marketing and content channels.
  • Partner with marketing and content decision science teams on content generation, channel optimization, attribution, and incrementality measurement.
  • Develop measurement and modeling capabilities for pharma direct partners, including incremental prescription lift, audience targeting, and campaign effectiveness, working with first and third party prescription, claims, and behavioral data.
  • Support employer direct initiatives with member engagement, utilization, and adoption modeling that strengthens our benefits and B2B offerings.
  • Refine our attribution and identity capabilities, applying NLP techniques such as text cleaning, normalization, and typo correction to improve data quality at scale.
  • Build predictive models using statistical and machine learning techniques across classification, regression, and disambiguation problems, owning the full lifecycle from problem framing and feature engineering through training, evaluation, deployment, monitoring, and retraining.
  • Lead experimentation strategy, including A/B testing design, causal inference approaches, and measurement frameworks that inform critical business decisions.
  • Define and drive the technical roadmap for decision science capabilities, introducing new methodologies, technologies, and best practices that improve team effectiveness and business outcomes.
  • Provide technical leadership and mentorship to data scientists, elevating analytical best practices and advising stakeholders to ensure technical rigor and sound decision-making.
  • Partner with the broader data team to improve data consistency, cleanliness, and ease of use, contributing to shared tooling, documentation, and standards that raise the bar across the organization, including model governance, reproducibility, and responsible AI.

Must-Have Qualifications
  • 8+ years of experience in data science, machine learning, operations research, or a related quantitative field, with a track record of delivering measurable business impact through productionized solutions. Experience in audience modeling, marketing analytics, attribution, or identity resolution is strongly preferred.
  • Proven track record of technical leadership, influencing business strategy, and driving adoption of advanced analytical approaches across organizations.
  • An undergraduate degree (or equivalent practical experience) in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, Operations Research, Data Science, or a closely related discipline.
  • Deep understanding of machine learning, statistical modeling, optimization techniques, causal inference, forecasting, experimentation, and predictive analytics.
  • Expertise in Python and common data science libraries (for example pandas, NumPy, scikit-learn, PySpark, TensorFlow, PyTorch, or similar).
  • Strong working knowledge of databases and distributed data systems such as Redshift, PostgreSQL, and Spark/EMR.
  • Experience building and deploying solutions using cloud platforms (AWS, GCP, or Azure) and modern data platforms such as Databricks.
  • Experience deploying, monitoring, and operationalizing machine learning models using modern MLOps practices, including experimentation platforms, feature stores, and model monitoring.
  • Experience evaluating and applying AI/ML solutions, including generative AI and large language model (LLM) technologies, where appropriate.
  • Comfort with ambiguity and the ability to thrive in a fast-paced, high-change environment. You are adaptable, intellectually curious, and open to new concepts, tools, and processes.
  • Strong communication skills, with the ability to influence technical and business stakeholders at multiple levels and to translate technical findings into clear, actionable recommendations for diverse audiences.
  • A collaborative, self-starting mindset. You are a team player who can operate independently, take ownership, and hit the ground running.

Nice-to-Have Qualifications
  • Prior exposure to the prescription, pharmacy, or broader healthcare industry.
  • Experience with marketing analytics, audience segmentation, attribution, or incrementality measurement.
  • Experience supporting pharma manufacturer or employer and benefits partners in a B2B analytics context.
  • Experience with recommendation systems, reinforcement learning, optimization engines, or decision science applications.
  • An advanced degree (Master's or PhD) in a quantitative field.
  • Experience contributing to patents, publications, open-source projects, or industry thought leadership.

What Success Looks Like
Within your first few months, you will ramp up on our data landscape and the audience, marketing, pharma direct, and employer direct problem spaces, ship your first production-influencing analysis or model, and build trusted partnerships across the data, product, and engineering teams. Over time, you will become a go-to expert on audience, identity, and marketing measurement modeling, and a meaningful contributor to GoodRx's mission of making healthcare affordable for everyone.
Engineering teams are responsible for supporting appropriate security controls, including management, operational, and technical controls in addition to general GoodRx best practices, such as reading and adhering to the security policies and procedures, being vigilant and observant of potential security threats, etc.
At GoodRx, pay ranges are determined based on work locations and may vary based on where the successful candidate is hired. The pay ranges below are shown as a guideline, and the successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, and other relevant business and organizational factors. These pay zones may be modified in the future. Please contact your recruiter for additional information.
San Francisco and Seattle Offices:
$202,000.00 - $323,000.00
New York Office:
$185,000.00 - $296,000.00
Santa Monica Office:
$168,000.00 - $269,000.00
Other Office Locations:
$151,000.00 - $242,000.00
GoodRx also offers additional compensation programs such as annual cash bonuses or commission, and annual equity grants for most positions as well as generous benefits. Our great benefits offerings include medical, dental, and vision insurance, 401(k) with a company match, an ESPP, unlimited vacation, 13 paid holidays, and 72 hours of sick leave. GoodRx also offers additional benefits like mental wellness and financial wellness programs, fertility benefits, generous parental leave, pet insurance, supplemental life insurance for you and your dependents, company-paid short-term and long-term disability, and more!
We're committed to growing and empowering a more inclusive community within our company and industry. That's why we hire and cultivate diverse teams of the best and brightest from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has a seat at the table and the tools, resources, and opportunities to excel.
With that said, research shows that women and other underrepresented groups apply only if they meet 100% of the criteria. GoodRx is committed to leveling the playing field, and we encourage women, people of color, those in the LGBTQ+ communities, individuals with disabilities, and Veterans to apply for positions even if they don't necessarily check every box outlined in the job description. Please still get in touch - we'd love to connect and see if you could be good for the role!
GoodRx is committed to providing reasonable accommodations for candidates with disabilities during our recruiting process. If you need any assistance or accommodations due to a disability, please reach out to us at accommodations@goodrx.com.
We prioritize candidate safety. Please be aware that all official communication will only be sent from @goodrx.com or goodrx@myworkday.com addresses.
GoodRx is America's healthcare marketplace. The company offers the most comprehensive and accurate resource for affordable prescription medications in the U.S., gathering pricing information from thousands of pharmacies coast to coast, as well as a tele-health marketplace for online doctor visits and lab tests. Since 2011, Americans with and without health insurance have saved $60 billion using GoodRx and million consumers visit goodrx.com each month to find discounts and information related to their healthcare. GoodRx is the #1 most downloaded medical app on the iOS and Android app stores. For more information, visit www.goodrx.com.