Senior Data Scientist

AbbVie • Mettawa, IL

7h

About The Position

AbbVie is seeking an experienced Senior Data Scientist to join its Analytics & AI organization and advance Copay Intelligence capabilities. The role develops AI and machine learning solutions to identify reimbursement and affordability program dynamics, improve patient access insights, and support proactive decision-making across patient support programs. It uses healthcare, claims, enrollment, and patient-level data to identify opportunities, uncover patterns, and produce actionable recommendations.

The Senior Data Scientist leads the design, development, deployment, and continuous improvement of analytics and AI solutions for strategic programs in predictive intelligence, healthcare affordability, patient access, and machine learning. The work spans the full AI and machine learning product lifecycle and requires technical expertise, business acumen, and the ability to turn complex analytical findings into practical solutions. The position works with data engineering, business stakeholders, technology teams, and analytics partners to transform large-scale healthcare data into scalable AI-powered solutions.

The role also contributes to production deployment, scalable machine learning workflows, monitoring and governance, and enterprise AI products. It serves as a data science subject matter expert, communicates insights to stakeholders and senior leadership, 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 are 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 working with large-scale data platforms and cloud-based environments.
• Familiarity with MLOps, model deployment, model monitoring, and production AI practices.
• Experience using modern software development and version control practices.
• Strong analytical and problem-solving capabilities.
• Excellent communication and stakeholder management skills.
• Ability to translate business challenges into data-driven solutions.
• Ability to work independently and collaborate effectively across teams.
• Strong organizational and project management skills.
• Passion for 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 cloud platforms such as 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 advanced machine learning and artificial intelligence models for healthcare affordability and copay intelligence initiatives.
• Build predictive models to identify patterns, risks, and opportunities using healthcare, claims, enrollment, and patient-level data.
• Design scoring frameworks, recommendation engines, and decision-support systems that enable proactive business actions.
• Evaluate and implement machine learning, deep learning, ensemble methods, graph analytics, and Generative AI approaches.
• Improve model performance through experimentation, feedback loops, and performance monitoring.
• 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 statistical and business outcome metrics.
• Translate analytical findings into recommendations for technical and non-technical stakeholders.
• Develop methods to measure the business impact and return on investment of analytical solutions.
• Partner with data engineering and technology teams to deploy machine learning solutions into production.
• 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 scale across business functions.
• Ensure solutions meet organizational quality, privacy, security, and compliance standards.
• Partner with business stakeholders to identify opportunities for AI and advanced analytics to deliver 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 broader analytics community.
• Stay current on emerging AI, machine learning, and healthcare analytics technologies and trends.

Benefits

• Paid time off, including vacation, holidays, and sick time.
• Medical, dental, and vision insurance for eligible employees.
• 401(k) for eligible employees.
• Eligible to participate in long-term incentive programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior