GoodRx is looking to solve the problem of healthcare affordability and access by leveraging data science to improve customer engagement, retention, and personalization across their products and marketplaces, and to develop innovative machine learning solutions.
Requirements
- Strong technical foundation in statistical modeling, ML algorithms (tree/forest methods, clustering, optimization, regression, neural networks), and experimentation.
- Hands-on experience with Python (pandas, numpy, scikit-learn, PyTorch/TensorFlow) and cloud-based big data ecosystems (AWS, Databricks, Redshift/BigQuery, Spark).
- Proven track record in delivering end-to-end data science models & systems (from development to production) at scale.
- Experience with deep learning for personalization, search, recommendation, Look-alikes, optimal pricing or multimodal (text, image, structured) data.
- Prior exposure to GenAI product strategy or large-scale applied ML infrastructure.
Responsibilities
- Build and oversee predictive models and advanced ML/AI systems (e.g., forecasting, recommendation, CTR/CVR modeling, customer segmentation).
- Develop state-of-the-art statistical and machine learning approaches, including pipelines that handle large-scale, high-dimensional datasets.
- Champion experimentation and rigorous evaluation methods to ensure models meet business and latency requirements.
- Explore new frontiers in GenAI, statistical genetics, and multimodal data (e.g., imaging, text, structured data) where relevant to GoodRx’s mission.
- Partner with product, engineering and marketing teams to translate business needs into robust technical solutions.
- Deliver data science products to improve customer engagement, retention, and personalization across products and marketplaces.
- Work with engineering teams to ensure scalable, reliable, and efficient deployment of data science solutions.
Other
- Provide leadership, mentorship, and coaching to data scientists; foster an environment of innovation, inclusion, and technical rigor.
- Support performance management, onboarding, and professional growth of team members.
- Define and drive organization-wide ML and analytics roadmaps, balancing near-term impact with long-term innovation.
- Excellent communication and stakeholder management skills; able to translate technical findings into business impact.
- Comfort with ambiguity and adaptability in a dynamic, high-change environment.
