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Director Impact Measurement Jobs (NOW HIRING)

Magellan AI

Measurement Growth Director

New York, NY · On-site +1

$70K - $110K/yr

Direct revenue impact : You'll be responsible for growing revenue within your accounts by increasing measurement adoption and usage, with clear targets tied to overage. * High-value relationships

Magellan AI

Measurement Growth Director

New York, NY · Remote

$70K - $110K/yr

Direct revenue impact : You'll be responsible for growing revenue within your accounts by increasing measurement adoption and usage, with clear targets tied to overage. * High-value relationships

Good Reason Houston

Chief Impact Officer

Houston, TX · On-site

The will directly manage three Managing Directors, leading a department of 20 team members ... Own enterprise impact measurement, evaluation frameworks, and performance reporting. * Lead and ...

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Director Impact Measurement information

What does a director of impact measurement do?

A Director of Impact Measurement is responsible for designing, implementing, and overseeing strategies to assess the effectiveness and outcomes of an organization’s programs or initiatives. They develop frameworks and tools to measure social, environmental, or economic impact, analyze data, and report findings to stakeholders. This role often involves collaborating with program teams, leadership, and external partners to ensure that impact measurement aligns with organizational goals and drives continuous improvement.

What are some common challenges faced by a director of impact measurement, and how can they be addressed?

A Director of Impact Measurement often encounters challenges such as aligning diverse stakeholders on what metrics truly reflect impact, ensuring data collection methods are consistent across programs, and communicating complex results in a clear, actionable way. To address these, it's important to establish transparent processes, foster collaboration across departments, and invest in staff training on data literacy. Regularly reviewing and refining measurement frameworks with input from both leadership and frontline teams also helps ensure the data remains relevant and actionable.

What are the key skills and qualifications needed to thrive as a director of impact measurement, and why are they important?

To thrive as a Director of Impact Measurement, you need expertise in data analysis, program evaluation, and a strong background in social sciences, statistics, or a related field, often supported by an advanced degree. Familiarity with data visualization tools, impact measurement frameworks (like Theory of Change or SROI), and advanced analytics software is typically required. Strong leadership, stakeholder engagement, and communication skills distinguish top performers in this role. These skills are crucial for accurately assessing program effectiveness, guiding organizational strategy, and effectively communicating impact to internal and external audiences.

What are popular job titles related to Director Impact Measurement jobs?

For Director Impact Measurement jobs, the most frequently searched job titles are:

Infographic showing various Director Impact Measurement job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution.

Director, Oncology Commercial Data Science & AI Products

Gaithersburg, MD • On-site

AstraZeneca
Pharmaceutical Product Wholesalers • 10K+ employees
Learn more about AstraZenecaexternal

Full-time

Re-posted 3 days ago

AstraZeneca rating

8.4

Company rating: 8.4 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

Job description

We're building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you'll actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real.
Our DS&AI Products team is the OBU's in-house engine for that work. We lead all aspects of the full lifecycle of AI-powered applications spanning predictive field triggers, patient-identification models, omnichannel next-best-action, KOL intelligence, and GenAI-powered field tools - and we ship products, not reports. Every capability we build must deliver measurable field adoption and commercial impact.
We are hiring a Director, DS&AI Products who will lead a multi-indication AI product portfolio end-to-end, serve as the strategic DS&AI business partner to OBU brand and medical leadership, and lead the responsible design, delivery, adoption, and impact measurement of AI solutions that drive commercial lift and better patient outcomes.
Role overview
This is a product ownership and program strategy role - not an analytics consulting role. You lead the full AI product lifecycle: problem definition, customer research, product requirements, AI development partnership, UX design alignment, deployment, change management, and post-launch impact measurement. You are the product owner and strategist for the AI capabilities powering Sales, Marketing, and Medical Affairs across your assigned OBU tumor areas, and the liaison US Oncology and the broader AstraZeneca Enterprise AI organization for customer engagement capability building.
You will be equally comfortable writing a product requirements document, reviewing a GenAI architecture with an engineering lead, running a discovery session with brand managers, delivering the AI transformation narrative to field sales leadership and presenting a capability roadmap to the Senior Leadership Teams. You will bring a platform-centric, reuse-first mindset: every solution you ship should be architected for scalability and accelerated deployment across indications - so a trigger framework proven in one tumor area becomes the template for the next launch.
Key responsibilities
1. Program Strategy & AI Roadmap Ownership
  • Own the strategy and transformation roadmap for Sales, Marketing, and Medical Affairs AI capabilities across your assigned OBU tumor-area portfolio, being responsible for planning and budget management processes in alignment with OBU annual cycle.

  • Develop quantifiable cases and value narratives for future Sales, Marketing, and field AI capabilities in collaboration with OBU Franchises, I&A, and Enterprise AI delivery teams; present to OBU Leadership Team (OLT) to drive top-down alignment and shared decisions on roadmap prioritization.

  • Maintain a prioritized product backlog with well-defined user stories, acceptance criteria, and delivery timelines; balance the portfolio across housekeeping (maintenance/refresh), innovation (new AI capability pilots), and new-indication onboarding in an agile operating model.

  • Track industry, market, and innovation shifts - GenAI, agentic AI, oncology data science, competitor AI strategies - to anticipate opportunities and risks and keep the roadmap forward-looking.

  • Champion a platform-centric, reuse-first architecture philosophy: design AI capabilities that pilot in one indication and scale across OBUs without re-platforming.

2. GenAI & Agentic AI Product Development
  • Lead the definition, design, and delivery of GenAI-powered applications for OBU commercial and medical teams: AI-assisted field briefing tools (InsightIQ), clinical evidence summarization for MSLs, agentic omnichannel workflows (Engagement IQ), and natural-language interfaces to AZBrain analytics.

  • Define product requirements and functional specifications for LLM-powered, RAG-based, and agentic AI applications; partner with Enterprise AI engineering leads to translate requirements into governed, scalable, production-grade solutions.

  • Maintain solid understanding of the evolving GenAI / agentic AI landscape - prompt engineering, RAG architectures, multi-agent orchestration, evals - and critically evaluate architecture choices against OBU field workflow requirements.

  • Apply rigorous pilot-and-scale methodology: define pilot scope and success criteria upfront, measure output quality and user adoption, and drive evidence-based scaling decisions to other indications and OBU functions.

3. DS&AI Business Partnership - Brand, Medical & Access
  • DS&AI business partner and product owner for assigned tumor-area brand teams, Medical Affairs, and Market Access - attending strategy reviews, launches, and leadership committee meetings as the AI expert at the table.

  • Lead cross-functional discovery workshops that reveal unmet decision needs. Develop well-scoped AI use cases using detailed problem descriptions, success metrics, data requirements, and risk tiers. Convert the results into actionable user stories for engineering teams.

  • Partner with MSL and medical leadership on scientific use cases: treatment-pathway analytics, KOL/KEE influence mapping (Cami constellation), diagnostics/biomarker testing strategies and health equity analytics.

  • Own and govern demand-sensing and care-gap workstreams feeding FSIP, forecasting, and field strategy plans; present roadmap and field impact at leadership team meetings, national sales meetings, and SteerCo forums.

4. Capability Building & Change Management
  • Set the direction for how OBU develops AI functions in Sales, Marketing, and Medical Affairs. Prioritize solutions that meet key business needs. Ensure these solutions are scalable, balanced, and embedded in daily field workflows.

  • Identify the people and process changes required to successfully stand up each AI capability; act as change leader, delivering the organizational AI transformation narrative to sales and marketing teams.

  • Partner with Business Excellence and Franchise teams to design and execute training plans, field enablement workshops, and persona-aligned onboarding for every major capability release.

  • Drive AI literacy across brand, medical, and field teams through capability reviews, lunch-and-learns, and executive presentations; build self-service fluency with AZ AI platforms.

5. Execution Excellence & Delivery Accountability
  • Ensure accurate and timely translation of business needs into technical requirements. Partner with the AI division passionate about enterprise solutions in data science and engineering. Establish clear RACI and maintain alignment on priorities, dependencies, and timelines across the full delivery model.

  • Drive launch-critical AI results on time: pre-launch analytics, ML-enriched targeting lists, EHR/claims/lab-signal predictive triggers per AIDLC framework.

  • Supervise progress and surface interdependencies across the product portfolio; creatively address key challenges and blockers and escalate to senior leadership with clear problem framing and proposed solutions.

  • Manage external vendors and consulting partners against defined deliverables and timelines; support budget management and PMO invoicing.

6. AI Innovation, Data Science & Emerging Capabilities
  • Identify and pilot emerging AI/ML techniques for the OBU portfolio: LLM-powered field tools, agentic frameworks, biomarker-signal models, multimodal data fusion (structured claims + unstructured clinical notes + lab signals), and RWE analytics.

  • Lead or co-lead data-source evaluations; articulate granularity caveats and preprocessing requirements to both technical and business audiences.

  • Design and implement the OBU predictive ML trigger ecosystem for earlier patient identification across indications, with reusable frameworks that scale across tumor areas.

  • Drive precision-medicine and earlier-patient-identification strategies: design AI trigger frameworks that detect high-risk patients upstream of clinical decision points, reducing diagnostic and treatment lag.

7. AI Governance, Compliance & Data Stewardship
  • Operate within AstraZeneca's enterprise AI governance framework: registry-before-scale, model and data cards, human-in-the-loop oversight, ongoing monitoring, and IT approval processes.

  • Navigate compliance requirements, data access controls, HIPAA privacy guardrails, and vendor management for all OBU AI use cases; ensure all products are deployed responsibly with appropriate documentation.

  • Partner with OBEX, FSIP, Legal, Privacy, and I&A to ensure AI-ready data assets (enriched claims, EHR, MMIT) are compliant, auditable, and operationalized with standardized QA and refresh cadences.

  • Maintain auditable AIDLC; govern UAT → compliance approval → release gates with scenario-based stakeholder demonstrations and documented acceptance criteria.

8. Impact Measurement & Value Tracking
  • Define success criteria and KPIs before launch; supervise adoption metrics (app utilization, trigger execution rate, noise reduction, coverage), output quality, and downstream business impact (sales lift, patient-identification speed, care-gap closure) post-launch.

  • Lead causal-impact assessments to quantify commercial lift attributable to triggers and AI applications; use findings to guide cross-OBU collaboration and investment decisions.

  • Communicate results to OBU and enterprise leadership with clarity - translating product performance data into business impact narratives that reinforce AI investment decisions and advise future roadmap prioritization.

Essential Requirements
  • Bachelor's degree or comparable experience in a quantitative field like CS, statistics, engineering, economics, or similar. Advanced qualifications, including an MBA, MS, PhD, or equivalent experience, are highly valued.

  • 7-10+ years of professional experience with 5+ years in pharma commercial functions (or pharma-focused strategy consulting); demonstrated end-to-end AI/data-science product ownership with measurable commercial impact in an oncology or specialty context.

  • Strong analytical fluency - able to translate between brand strategy, commercial operations, data science, and technology teams; experienced at bridging business and technical stakeholders across a highly matrixed organization.

  • Hands-on familiarity with LLMs, crafting input queries, retrieval-augmented generation systems, and agentic frameworks (LangChain, LlamaIndex, or equivalent); working proficiency in Python and ML/AI tooling; experience with cloud platforms (AWS SageMaker/Athena, Databricks, Azure, or GCP).

  • Deep expertise in oncology commercial data: secondary claims (IQVIA, Symphony, MMIT), EHR/EMR sources such as Komodo and Veeva PULSE, lab/diagnostic data (Diaceutics), specialty pharmacy, and enriched ML assets.

  • Exceptional communication skills and proven track record to operate successfully in highly matrixed organizations; effective interpersonal and relationship-management skills with a consultative approach.

  • Strong initiative: ability to understand core business goals, set direction, build alignment, and drive work forward proactively; resourceful and influential in a fast-growing organization.

Preferred Qualifications
  • Graduate degree (MBA, MS, MD, or PhD) in a quantitative, scientific, or business discipline.

  • Demonstrated commercial experience in Oncology

  • Production GenAI / agentic AI experience in commercial pharma: LLM-powered field tools, RAG-based clinical applications, or agentic omnichannel workflow automation under enterprise governance.

  • Experience with KOL/KEE influence analytics, precision-targeting tools (e.g., EGFR-testing waypoint analysis), or omnichannel NBA platforms (Aktana, Veeva Align).

  • Track record of leading AI-enabled business transformation and change management programs across large organizations (1,000+ users).

  • External thought leadership: conference presentations or publications in oncology analytics or commercial AI

Technical competency profile
Ideal candidates will demonstrate applied depth across:
GenAI & Agentic AI
  • LLMs and prompt engineering: GPT-4 / Claude / Gemini family; system prompting, few-shot, chain-of-thought, structured output

  • RAG architectures: vector stores, chunking strategies, retrieval evaluation, hallucination mitigation

  • LLMOps: evaluation pipelines, output quality monitoring, A/B testing for GenAI applications

Classical ML & Data Science
  • Supervised/unsupervised learning: logistic regression, gradient boosting (XGBoost/LightGBM), clustering, propensity scoring for patient/HCP targeting

  • Time-series and sequence models for patient-journey stage prediction and trigger timing optimization

  • Causal inference and test-and-control methodologies for AI impact attribution and c

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About AstraZeneca

Sourced by ZipRecruiter

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies. A place built on courage, curiosity and collaboration - we make bold decisions driven by patient outcomes. Empowered to lead at every level, free to ask questions and take smart risks that write the next chapter for our pipeline and Oncology team. Make a meaningful impact that brings real benefits to society. By applying your knowledge of data, you will help to redefine our industry and ultimately save lives. Work with experts who share a common goal: to accelerate the potential of medicines and the science of tomorrow.

Industry

Pharmaceutical product wholesalers and pharmaceutical and medicine manufacturing

Company size

10,000+ Employees

Headquarters location

Cambridge, Cambridgeshire, GB

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