Senior Data Scientist
About The Position
AbbVie is seeking an experienced Senior Data Scientist for its Analytics & AI organization to advance Copay Intelligence capabilities. The role develops AI and machine-learning solutions that identify reimbursement and affordability program dynamics, improve patient-access insights, and support proactive decisions across patient support programs. It uses healthcare, claims, enrollment, and patient-level data to uncover patterns, identify opportunities, and generate actionable recommendations. The Senior Data Scientist leads the design, development, deployment, and continuous improvement of advanced analytics and AI solutions. Working across the full lifecycle of AI and machine-learning product development, the position collaborates with data engineering, business stakeholders, technology teams, and analytics partners to turn large-scale healthcare data into scalable solutions with measurable business impact. The role also contributes subject-matter expertise, presents findings to leadership and cross-functional teams, and mentors junior data scientists.
Requirements
- Bachelor's degree in Statistics, Computer Science, Data Science, Mathematics, Engineering, Economics, Operations Research, or a related quantitative discipline; equivalent combinations of education, specialized training, and relevant professional experience will be considered.
- At least 6 years of experience developing and deploying machine-learning, artificial-intelligence, or advanced analytics solutions in production environments.
- Strong proficiency in Python and SQL.
- Hands-on experience with machine-learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
- Experience building predictive, classification, forecasting, recommendation, or optimization models.
- Strong knowledge of statistics, experimentation, predictive modeling, and model evaluation techniques.
- Experience with large-scale data platforms and cloud-based environments.
- Familiarity with MLOps, model deployment, model monitoring, and production AI practices.
- Experience with modern software development and version control practices.
- Strong analytical and problem-solving capabilities.
- Excellent communication and stakeholder-management skills, including the ability to translate business challenges into data-driven solutions.
- Ability to work independently and collaborate effectively across teams.
- Strong organizational and project-management skills.
- Interest in innovation, continuous learning, and practical application of AI technologies.
Nice To Haves
- Advanced degree (Master's or PhD).
- Experience with healthcare, pharmaceutical, claims, payer, patient support, or market access data.
- Experience developing AI-powered decision-support systems.
- Experience with AWS, Azure, or Google Cloud.
- Experience with Snowflake, Databricks, Spark, or other large-scale data environments.
- Experience deploying Generative AI or Large Language Model solutions.
- Experience in regulated industries where data quality, governance, and validation are critical.
Responsibilities
- Develop machine-learning and artificial-intelligence models for healthcare affordability and Copay Intelligence initiatives.
- Build predictive models using healthcare, claims, enrollment, and patient-level data to identify patterns, risks, and opportunities.
- Design scoring frameworks, recommendation engines, and decision-support systems that enable proactive business actions.
- Evaluate and implement machine-learning, deep-learning, ensemble, graph analytics, and Generative AI methodologies.
- Improve model performance through experimentation, feedback loops, and performance monitoring.
- Analyze complex healthcare datasets and conduct feature engineering, predictive modeling, forecasting, segmentation, optimization, and statistical analyses.
- Assess model performance using statistical and business outcome metrics; translate findings into recommendations for technical and non-technical stakeholders.
- Develop methods to measure business impact and return on investment for analytical solutions.
- Partner with data engineering and technology teams to deploy machine-learning solutions into production.
- Design scalable, maintainable machine-learning workflows and pipelines; implement model monitoring, automated retraining, governance, and performance management processes.
- Support development of enterprise AI products that can scale across business functions, ensuring quality, privacy, security, and compliance standards are met.
- Partner with business stakeholders to identify opportunities for AI and advanced analytics to create measurable value.
- Serve as a subject-matter expert in data science, machine learning, and predictive analytics; present findings and technical concepts to senior leadership and cross-functional teams.
- Mentor junior data scientists and contribute to the broader analytics community.
- Keep current with emerging AI, machine-learning, and healthcare analytics technologies and trends.
Benefits
- Paid time off, including vacation, holidays, and sick leave.
- Medical, dental, and vision insurance for eligible employees.
- 401(k) for eligible employees.
- Eligible to participate in long-term incentive programs.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
