below marketmost similar roles pay hereabove market
This role pays less than
53%
of similar roles. Most pay
$126,800–$189,187
— the blue band above.
At the midpoint, this role pays about
$159k
versus about
$158k
for comparable roles.
Based on 240 similar postings.
Employer
About AbbVie
AbbVie is a global biopharmaceutical company focused on discovering and delivering innovative medicines and solutions in immunology, oncology, neuroscience, and eye care. Its products include Humira, Skyrizi, and Rinvoq.
AbbVie currently has
145 open roles
on FindRole.
Listed pay typically runs
$109,500–$208,500
across 140 roles with salary data.
The Senior Data Scientist joins the Analytics & AI organization to advance Copay Intelligence capabilities. This role involves developing innovative machine learning and artificial intelligence solutions to identify complex reimbursement and affordability program dynamics while improving patient access insights. The successful candidate will build predictive intelligence products using healthcare, claims, enrollment, and patient-level data to uncover hidden patterns and generate actionable recommendations. Key responsibilities include designing scoring frameworks, recommendation engines, and decision-support systems. Required technical skills include proficiency in Python and SQL, along with experience using frameworks like Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch. The role addresses the business problem of enhancing copay program intelligence and healthcare affordability through scalable AI-powered solutions, utilizing advanced methodologies such as deep learning, graph analytics, and Generative AI.
What does a Data Scientist earn?
Median $173200 from 338 postings across 66 companies.
Develop advanced machine learning and AI models to support healthcare affordability and copay intelligence initiatives.
Build predictive models to identify patterns, risks, and opportunities from healthcare, claims, and patient-level data.
Design scoring frameworks, recommendation engines, and decision-support systems to enable proactive business actions.
Analyze large healthcare datasets to perform feature engineering, forecasting, segmentation, and statistical analyses.
Partner with data engineering teams to deploy scalable machine learning workflows and production pipelines.
Implement model monitoring, automated retraining, and governance processes to ensure solution quality and compliance.
Translate complex analytical findings into clear, actionable recommendations for technical and non-technical stakeholders.
Mentor junior data scientists and serve as a subject matter expert in predictive analytics.
What we're looking for
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.
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 working with large-scale data platforms, cloud-based environments, and MLOps practices.
Experience working with healthcare, pharmaceutical, claims, payer, patient support, or market access data (preferred).
Experience deploying Generative AI or Large Language Model solutions (preferred).
Media Mix Modeling
Multi Touch Attribution
SQL
Python
R
Databricks
BigQuery
Machine Learning
Multivariate Regression
Optimization Algorithms
Generative AI
RShiny
Ads Data Hub
Data Science