Lead Data Scientist

GoodRx, Inc.; United States; On-site; USD 170,000 - 290,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) with company match

Unlimited vacation

13 paid holidays

Job summary

GoodRx, Inc. is seeking a Lead Data Scientist to shape responsible AI and ML workflows across the organization. You will design, build, and deploy models that affect how GoodRx reaches consumers and partners.

You will collaborate with data scientists, engineers, product managers, and business stakeholders to drive measurable impact through audience modeling, marketing analytics, attribution, and identity resolution while advancing model governance and reproducibility.

Qualifications

• 8+ years of experience in data science, machine learning, or related quantitative field.
• Experience in audience modeling, marketing analytics, attribution, or identity resolution preferred.
• Proven technical leadership, influencing strategy and adoption of advanced analytics.
• Undergraduate degree in a quantitative field (Statistics, Math, CS, Economics, OR, Data Science).
• Deep understanding of ML, modeling, optimization, causal inference, forecasting, experimentation, and predictive analytics.
• Expertise in Python and common data science libraries (pandas, NumPy, scikit-learn, PySpark, TensorFlow, PyTorch).
• Strong knowledge of databases and distributed data systems (Redshift, PostgreSQL, Spark/EMR).
• Experience with cloud platforms (AWS, GCP, Azure) and data platforms like Databricks.
• Experience deploying ML models with MLOps, experimentation platforms, feature stores, and monitoring.
• Experience evaluating AI/ML solutions including generative AI and LLMs.

Responsibilities

• Lead complex data science initiatives across audience decisioning and marketing analytics, driving business impact.
• Derive insights from large datasets to map user journeys from online to in-store behavior.
• Build audience segmentation, propensity, and lookalike models for cross-channel targeting.
• Collaborate with marketing and content teams on content generation, attribution, and incrementality.
• Develop measurement and modeling capabilities for pharma direct partners and employer direct analytics.
• Support employer direct initiatives with engagement and adoption modeling.
• Refine attribution and identity capabilities using NLP techniques for data quality at scale.
• Develop predictive models across classification, regression, and disambiguation with end-to-end lifecycle ownership.
• Lead experimentation strategy, including A/B testing and causal inference frameworks.
• Define technical roadmap for decision science capabilities and best practices.
• Provide technical leadership and mentorship to data scientists and stakeholders.
• Improve data consistency and tooling across the team, including governance and reproducibility.

Skills

Audience modeling

Marketing analytics

Attribution

Identity resolution

Technical leadership

Python

Data science libraries

Education

Bachelor's degree in a quantitative field

Tools

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

PySpark

Databricks

Redshift

PostgreSQL

Spark/EMR

AWS

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'll 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.

• 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.

You help establish and evolve best practices for responsible AI development, model governance, and reproducibility across the organization.

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.

Compensation

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.

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.

Benefits

• medical insurance
• dental insurance
• vision insurance
• 401(k) with a company match
• ESPP
• unlimited vacation
• 13 paid holidays
• 72 hours of sick leave
• mental wellness
• 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!

Company Culture & Inclusion

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 [e-mail].

We prioritize candidate safety. Please be aware that all official communication will only be sent from @goodrx.com or [e-mail] 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. We help Americans get the healthcare they need at a price they can afford. We believe everyone deserves affordable and convenient healthcare. We build better ways for people to find the best care at the best price. Our technology gives all Americans — regardless of income or insurance status — the knowledge, choice, and care they need to stay healthy. We’re here to help. Come and help us create the future of healthcare.