Principal Data Scientist
AbbVie
August 20, 2026
Remote friendly (Mettawa, IL)
United States
$124,500 - $236,500 USD yearly
IT
Principal Data Scientist — Key Responsibilities
- Lead a portfolio of advanced analytics across customer understanding, engagement planning, decision support, and measurement.
- Translate product requirements/business goals into scalable technical solutions (model design, feature engineering, validation, deployment).
- Design predictive and inferential models using complex, multi-source data to generate actionable insights on customer behavior and business performance.
- Evaluate cross-channel engagement patterns, interaction effects, and temporal dynamics.
- Own measurement methodologies to assess effectiveness, incrementality, and business impact using experimental/observational methods.
- Partner with BTS, Digital Lab, engineering, and platform teams to build production-ready analytics and AI/ML solutions.
- Establish best practices for model development (code quality, documentation, reproducibility, peer review, version control, rigor).
- Communicate complex findings into actionable recommendations.
- Productionalize AI/ML solutions (deployment, monitoring, lifecycle management).
- Stay current with applied ML, causal inference, and pharmaceutical analytics; pilot emerging methods.
Supervisory/Management
- No formal direct reports; provide technical mentorship and may lead workstreams with external vendors.
Qualifications (Required/Strongly Preferred)
- BS in quantitative field required; MS/PhD strongly preferred.
- 8+ years data science/ML/advanced analytics; production-quality models.
- 5+ years pharma/biotech/healthcare/life sciences commercial analytics (highly preferred).
- 4+ years omnichannel analytics; and 4+ years measuring commercial effectiveness (A/B, closed-loop, quasi-experimental).
- Strong Python and/or R; strong SQL; hands-on pandas/NumPy/scikit-learn/PySpark.
- Deep learning experience (PyTorch/TensorFlow) for temporal/sequential/recommendation use cases.
- Experience productionizing AI/ML in cloud.
Preferred
- RL, multi-armed bandits, transformers; pharma data sources (IQVIA/Symphony Health/APLD); agile; Azure ML/Databricks/MLflow; LLM workflows/agentic AI; API/pipeline integration.
Benefits
- Paid time off; medical/dental/vision insurance; 401(k) (eligible employees). Long-term incentive program eligibility.
- Lead a portfolio of advanced analytics across customer understanding, engagement planning, decision support, and measurement.
- Translate product requirements/business goals into scalable technical solutions (model design, feature engineering, validation, deployment).
- Design predictive and inferential models using complex, multi-source data to generate actionable insights on customer behavior and business performance.
- Evaluate cross-channel engagement patterns, interaction effects, and temporal dynamics.
- Own measurement methodologies to assess effectiveness, incrementality, and business impact using experimental/observational methods.
- Partner with BTS, Digital Lab, engineering, and platform teams to build production-ready analytics and AI/ML solutions.
- Establish best practices for model development (code quality, documentation, reproducibility, peer review, version control, rigor).
- Communicate complex findings into actionable recommendations.
- Productionalize AI/ML solutions (deployment, monitoring, lifecycle management).
- Stay current with applied ML, causal inference, and pharmaceutical analytics; pilot emerging methods.
Supervisory/Management
- No formal direct reports; provide technical mentorship and may lead workstreams with external vendors.
Qualifications (Required/Strongly Preferred)
- BS in quantitative field required; MS/PhD strongly preferred.
- 8+ years data science/ML/advanced analytics; production-quality models.
- 5+ years pharma/biotech/healthcare/life sciences commercial analytics (highly preferred).
- 4+ years omnichannel analytics; and 4+ years measuring commercial effectiveness (A/B, closed-loop, quasi-experimental).
- Strong Python and/or R; strong SQL; hands-on pandas/NumPy/scikit-learn/PySpark.
- Deep learning experience (PyTorch/TensorFlow) for temporal/sequential/recommendation use cases.
- Experience productionizing AI/ML in cloud.
Preferred
- RL, multi-armed bandits, transformers; pharma data sources (IQVIA/Symphony Health/APLD); agile; Azure ML/Databricks/MLflow; LLM workflows/agentic AI; API/pipeline integration.
Benefits
- Paid time off; medical/dental/vision insurance; 401(k) (eligible employees). Long-term incentive program eligibility.