Senior Data Scientist

Job Description

AbbVie is seeking an experienced Senior Data Scientist to join our Analytics & AI organization and help advance the next generation of Copay Intelligence capabilities.

This role will focus on developing innovative machine learning and artificial intelligence solutions that help identify complex reimbursement and affordability program dynamics, improve patient access insights, and drive more proactive decision-making across patient support programs.

The successful candidate will play a key role in building predictive intelligence products that leverage healthcare, claims, enrollment, and patient-level data to identify emerging opportunities, uncover hidden patterns, and generate actionable recommendations. These capabilities support a long-term strategy to enhance copay program intelligence, improve affordability insights, and strengthen data-driven decision-making across the organization.

Working closely with data engineering, business stakeholders, technology teams, and analytics partners, this individual will help transform large-scale healthcare data into scalable AI-powered solutions that create measurable business impact.

What You'll Be Doing

The Senior Data Scientist will lead the design, development, deployment, and continuous improvement of advanced analytics and AI solutions supporting AbbVie's Copay Intelligence initiatives. This individual will work on highly visible strategic programs focused on predictive intelligence, healthcare affordability analytics, patient access insights, and advanced machine learning applications. The role requires a combination of strong technical expertise, business acumen, and the ability to translate complex analytical findings into practical solutions. The ideal candidate is passionate about solving challenging problems with data and enjoys working across the full lifecycle of AI and machine learning product development.

Core Responsibilities

AI & Machine Learning Development

• Develop advanced machine learning and artificial intelligence models that support healthcare affordability and copay intelligence initiatives.
• Build predictive models that identify patterns, risks, and opportunities from healthcare, claims, enrollment, and patient-level data.
• Design scoring frameworks, recommendation engines, and decision-support systems that enable proactive business actions.
• Evaluate and implement modern AI methodologies, including machine learning, deep learning, ensemble methods, graph analytics, and Generative AI approaches.
• Continuously improve model performance through experimentation, feedback loops, and performance monitoring.

Advanced Analytics

• Analyze large and complex healthcare datasets to uncover actionable business insights.
• Perform feature engineering, predictive modeling, forecasting, segmentation, optimization, and statistical analyses.
• Assess and monitor model performance using both statistical and business outcome metrics.
• Translate analytical findings into clear recommendations for technical and non-technical stakeholders.
• Develop methodologies to measure business impact and return on investment for analytical solutions.

AI Product Development & Operationalization

• Partner with data engineering and technology teams to deploy machine learning solutions into production environments.
• Design scalable and maintainable machine learning workflows and pipelines.
• Implement model monitoring, automated retraining, model governance, and performance management processes.
• Support development of enterprise AI products that can be scaled across multiple business functions.
• Ensure solutions adhere to organizational standards for quality, privacy, security, and compliance.

Collaboration & Leadership

• Partner with business stakeholders to identify opportunities where AI and advanced analytics can drive measurable value.
• Serve as a subject matter expert in data science, machine learning, and predictive analytics.
• Present findings, recommendations, and technical concepts to senior leadership and cross-functional teams.
• Mentor junior data scientists and contribute to the growth of the broader analytics community.
• Stay current on emerging technologies and industry trends in AI, machine learning, and healthcare analytics.

Qualifications

Education & Experience

• Bachelor's degree in Statistics, Computer Science, Data Science, Mathematics, Engineering, Economics, Operations Research, or a related quantitative discipline.
• Advanced degree (Master's or PhD) is preferred but not required.
• Equivalent combinations of education, specialized training, and relevant professional experience will be considered.
• 6+ years of experience developing and deploying machine learning, artificial intelligence, or advanced analytics solutions in production environments.

Technical Skills

• Strong proficiency in Python and SQL.
• Hands-on experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.

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