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About the Role
The Data Scientist is a hands-on individual contributor supporting the analytical work of the Vice President, Data Science. You will work directly on the VP's projects, turning them into rigorous, well-documented analysis, models, and deliverables that support pharmaceutical, biotech, and medical technology clients. This role suits someone who thrives in an ambiguous, fast-moving environment, comfortable working from partial direction and making reasonable assumptions.
Responsibilities
- Build, test, and refine machine learning models and predictive analytics solutions for life sciences commercial and marketing challenges.
- Contribute across the ML pipeline — data acquisition, feature engineering, model training, and validation.
- Work within a complex, multi-source data environment — claims, prescribing, real-world, and consumer data.
- Monitor data quality and maintain data science pipelines for client data assets.
- Maintain analytical quality, reproducibility, and clear documentation across your own work.
- Build and maintain HCP targeting and segmentation models using NPI-level physician data, prescribing and treatment trends, and specialty-level behavioral signals.
- Develop patient and consumer audience models spanning condition-level segmentation, patient journey and line-of-therapy analytics, adherence prediction, and behavioral propensity scoring.
- Integrate and analyze real-world datasets to generate insights that are both scientifically rigorous and commercially actionable.
- Scale and deploy custom audiences across marketing activation platforms and publishers, working within privacy-safe, de-identified, and clean room environments.
- Take inputs and direction from brand and account teams and translate them into well-scoped analyses.
- Collaborate with audience strategy, media and marketing activation, and account teams to support the development of client recommendations.
- Summarize findings and model results for senior team members and internal stakeholders, and contribute to client-facing materials.
- Work collaboratively with teammates across data, engineering, and technology to bring analytical solutions into practice.
- Contribute to strong team practices by documenting your work, following shared standards, and creating reusable code and tools.
- Stay curious about emerging AI and machine learning approaches, and share ideas that could strengthen our work.
- Take ownership of your projects while communicating openly about progress, priorities, and where you may need support.
Requirements
- 3+ years of experience in data science, predictive analytics, or a related quantitative discipline.
- Working proficiency in Python and/or R for machine learning and statistical modeling.
- Solid SQL skills for querying large, complex datasets.
- Experience building ML models — supervised and unsupervised methods, classification, regression, clustering, and propensity modeling.
- Exposure to production deployment.
- Strong communication and data storytelling skills; able to translate complex analytical findings into clear, actionable recommendations for commercial and marketing stakeholders.
- Comfort operating in an ambiguous, fast-changing environment — able to act on incomplete direction, ask the right clarifying questions, and make progress independently while keeping senior stakeholders informed.
Skills
- Python
- R
- SQL
- Machine learning
- Predictive analytics
- Supervised learning
- Unsupervised learning
- Classification
- Regression
- Clustering
- Propensity modeling
- Data acquisition
- Feature engineering
- Model training
- Model validation
- Data quality monitoring
- Data science pipelines
- HCP targeting
- Segmentation
- Patient journey analytics
- Adherence prediction
- Behavioral propensity scoring
- Real-world data integration
- Marketing activation platforms
- Privacy-safe environments
- De-identified data
- Clean room environments
- Emerging AI
- Machine learning approaches
- Generative AI
- LLM-based applications
- Agentic workflows
- Emerging AI tooling
Experience Level
- 3+ years of experience
Education Level
- Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field (Master's preferred)
Salary/Compensations
- USD $112,290.00 - USD $179,712.00/Annually
Benefits
- Medical coverage
- Dental
- Vision
- Disability
- 401K
- Parental and family care leave
- Family forming assistance
- Tuition reimbursement
- Flexible time off
About the Company
- Publicis Groupe is a global leader in communication and is positioned at every step of the value chain, from consulting to execution, combining marketing transformation and digital business transformation.
- Through a unified and fluid organization, Publicis Groupe partners with its clients across communication, media, data and technology to ensure access to the full breadth of capabilities in every market.
- Present in over 100 countries, Publicis Groupe employs around 103,000 professionals.
Equal Opportunity
- All your information will be kept confidential according to EEO guidelines.
- Veterans Encouraged to Apply.