Associate Director, Advanced Analytics, Patient Journey Insights, Predictive Modeling

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the design and implementation of analytics focused on the patient journey, pinpointing critical intervention moments, access challenges, treatment transitions, adherence issues, persistence opportunities, and unmet needs within key therapeutic areas.

• Integrate and analyze longitudinal data sources from healthcare, including claims, prescriptions, specialty pharmacy, electronic health records (EHR), laboratory data, real-world evidence, clinical trial operations data, market access information, and third-party syndicated datasets.

• Create predictive models and employ machine learning techniques to aid in patient identification, biomarker status assessment, provider opportunity evaluation, treatment progression tracking, adherence risk analysis, clinical trial acceleration, and prioritizing engagement.

• Convert model outputs and findings related to the patient journey into concise recommendations, decision frameworks, dashboards, and executive-ready narratives tailored for stakeholders in Commercial, Medical Affairs, and Clinical Operations.

• Identify actionable AI and advanced analytics use cases, such as generative AI, natural language processing, intelligent automation, and decision intelligence, to enhance insight generation and operational efficiency.

• Act as a subject matter expert in patient journey insights and predictive modeling, assisting business, medical, and clinical stakeholders in transforming strategic inquiries into analytical methodologies, data needs, and measurable outcomes.

• Collaborate with teams in Commercial, Medical Affairs, Clinical Operations, Market Access, Medical Excellence, Clinical Development, Data Engineering, IT, Legal, Privacy, and Compliance to ensure that analytics solutions are relevant, precise, scalable, and suitable for a regulated life sciences setting.

• Present complex analytical results in a clear and engaging manner through presentations, dashboards, data narratives, and decision-support materials for senior stakeholders and cross-functional teams.

• Advocate for responsible AI and model governance practices by promoting transparency, explainability, bias awareness, human oversight, fit-for-purpose validation, and appropriate documentation for AI-driven decision support.

• Lead cross-functional analytics initiatives from problem definition and data evaluation through modeling, insight generation, stakeholder review, and implementation assistance.

• Offer technical guidance and mentorship to analysts, data scientists, and external partners to enhance analytical rigor, reproducibility, and relevance to business needs.

• Establish practical standards, reusable frameworks, and best practices for patient journey analytics, predictive modeling, model monitoring, and insight dissemination.

• Encourage the adoption of analytics by boosting stakeholder confidence, enhancing analytics literacy, and integrating insights into commercial planning, medical strategy, evidence generation, and clinical operations execution.

• Continuously seek opportunities to modernize tools, data assets, workflows, and AI-enabled processes to enhance the speed, quality, and scalability of analytics delivery.

⛳️ Requirements

• A Bachelor’s degree in a quantitative discipline such as biostatistics, statistics, mathematics, economics, data science, computer science, or a related field is required; an advanced degree is preferred.

• A BA/BS degree combined with 10+ years of overall experience, including 7+ years in advanced analytics, data science, patient journey analytics, commercial analytics, medical analytics, clinical operations analytics, or a similar role in the pharmaceutical, biotech, healthcare, or life sciences sectors.

• Proven experience in analyzing longitudinal healthcare data and generating actionable insights related to patient journeys across diagnosis, treatment, access, adherence, persistence, provider engagement, or clinical trial advancement.

• Hands-on experience in constructing, interpreting, and operationalizing predictive models or machine learning solutions utilizing healthcare, real-world, commercial, medical, or clinical operations data.

• A strong grasp of relevant data sources, including claims, prescriptions, specialty pharmacy, EHR, laboratory data, real-world data, clinical trial operations data, market access data, and third-party syndicated datasets.

• Proficiency in translating complex analytics into clear recommendations for senior stakeholders across Commercial, Medical Affairs, Clinical Operations, technology, data, legal, compliance, and vendor teams.

• Familiarity with responsible AI, model governance, validation, explainability, and the appropriate use of AI-driven decision-support tools in a regulated environment.

• A Bachelor’s degree in statistics, data science, economics, engineering, business analytics, computer science, public health, epidemiology, or a related quantitative field, or equivalent practical experience.

🏝️ Benefits

• Medical

• Dental

• Vision

• 401(k)

• FSA/HSA

• Life Insurance

• Paid Time Off

• Wellness