About The Position

The Market Access and Patient Services (MAPS) organizations are responsible for providing exceptional patient experiences through the identification and execution of resources to support patients throughout their treatment journey. The MAPS APEX function serves as the catalyst for understanding the patient’s treatment experience and developing analytical resources to support the APS team. The Senior Manager, Neuroscience, Oncology & Eye Care Access, Reimbursement & Fulfillment Analytics position will deliver high-quality analytics and applied data science solutions in support of the Access, Reimbursement and Fulfillment team within MAPS APEX. It will focus on Patient Support Program services, including Copay, Field Reimbursement Managers (FRMs) and Prior Authorization enablement. A core focus will be on improving and optimizing patient conversion, building and deploying predictive and machine learning models that improve patient conversion and help identify, reduce or eliminate any relevant barriers related to patient access through patient journey tracking.

Requirements

  • Bachelor’s Degree required, with a concentration in Business, Analytics, Economics, Mathematics, Statistics, Engineering or a related discipline.
  • This position requires 7+ years of experience in quantitative analysis of operational, sales or marketing data, and the ability to utilize data to develop business plans and strategies to better optimize a patient or customer funnel
  • Hands-on experience building, validating, and deploying predictive models using techniques such as logistic regression, gradient boosting (XGBoost/LightGBM), random forests or clustering
  • Must exhibit proficiency commensurate with Manager level in the following competencies: anticipate future needs, build collaborative partnerships, design, and implement innovative solutions, demystify complex information, communicate insights and solutions
  • Self-driven, intellectually curious and independent mindset, comfortable assessing unexplored or imperfect data landscapes, and has instinctive intuition for associating data back to relevant business needs
  • Proficiency in Python or R required, with demonstrated experience using ML libraries such as scikit-learn, XGBoost, or equivalent

Nice To Haves

  • Master’s Degree in a quantitative or data science field a plus
  • Knowledge and understanding of pharma ecosystem and datasets including physician-level prescribing, institutional sales data, payer-prescriber-level data, formulary data, Symphony/IQVIA claims, etc. is preferred
  • familiarity with MLflow, Databricks, or cloud-based ML platforms (Azure ML, AWS SageMaker) a plus
  • Experience with NLP libraries or text analytics (e.g., spaCy, NLTK, or LLM-based approaches) a plus
  • BI tool (Qlik/Tableau/Power BI) and DB query language (SQL/HIVE/IMPALA) knowledge preferred

Responsibilities

  • Contribute to mapping patient journey workflows and flag barriers to patient access, leveraging machine learning techniques as needed such as patient dropout prediction, conversion likelihood scoring, and prior authorization approval modeling to surface non-obvious patterns
  • Develop and maintain advanced analytical solutions including supervised and unsupervised ML models, statistical models, and segmentation frameworks that explain drivers and barriers impacting patient outcomes
  • Manage and provide the needed data related support for the development of dashboards that provide visibility into the performance of access solutions, including Copay, FRMs and Prior Authorization enablement
  • Utilize third party vendors such as IQVIA, Symphony, Relay Health and CoverMyMeds to facilitate and accelerate the patient journey
  • Identify and escalate key business issues related to program execution and performance, ensuring that multiple partners/stakeholder perspectives are considered
  • Support integration with Market Access and Brand APEX teams with respect to Access, Reimbursement & Fulfillment – onboard and drive adoption of new best in class tools/capabilities including ML-driven solutions developed in cooperation with relevant stakeholders
  • Collaborate closely with Copay Center of Excellence (CCOE), AbbVie Patient Services, Data Operations, BTS and Brand teams, communicating gaps in data reliability, timeliness, metric hygiene, and contributing to the improvement of the overall analytics ecosystem
  • Support CCOE team with copay forecasting capabilities, generating insights to effectively communicate impacts from copay design changes, or from industry or competitor actions
  • Partner with Data Operations and BTS to support putting models into production, monitoring, and retraining workflows, ensuring deployed models remain consistent over time
  • Leverage innovative, sophisticated analytic models that address critical issues but also meet key business criteria (e.g. cost, risk, business impact) and key technical criteria (e.g. reliability, validity, and predictability)
  • Work with contractors and external suppliers

Benefits

  • paid time off (vacation, holidays, sick)
  • medical/dental/vision insurance
  • 401(k)
  • long-term incentive programs
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