Director, Decision Intelligence & AI Product Strategy

📍 Job Overview

Job Title: Director, Decision Intelligence & AI Product Strategy

Company: Bayer

Location: Whippany, New Jersey, United States

Job Type: Full-Time

Category: Decision Intelligence / AI Product Strategy (with strong Revenue Operations and GTM implications)

Date Posted: 2026-08-12

Experience Level: 10+ years

Remote Status: Remote OK (residence-based candidates in the US considered)

🚀 Role Summary

• Lead the strategic direction and analytical architecture for Decision Intelligence (DI) and AI initiatives within the US Asundexian Product Squad, directly impacting Go-To-Market (GTM) strategies and revenue generation.

• Translate complex business decisions into actionable analytical blueprints, defining the necessary evidence, data, methods, and KPIs to drive informed decision-making.

• Drive the full lifecycle of decision products, from initial framing and analysis to deployment, adoption, and continuous improvement, ensuring measurable business value and competitive advantage.

• Serve as a senior strategic advisor to Product leadership, shaping the product's decision agenda and prioritizing initiatives based on their potential business impact and strategic importance.

• Synthesize insights from diverse data sources, conduct sophisticated analyses (e.g., patient journey mapping, segmentation, competitive intelligence), and generate breakthrough insights to inform commercial and strategic planning.

📝 Enhancement Note: While the title mentions "Product Strategy," the core responsibilities and required skills strongly align with a senior role in Decision Intelligence or advanced analytics within a commercial operations context, particularly within the pharmaceutical sector. This role is crucial for informing GTM strategies, sales effectiveness, and ultimately, revenue growth by optimizing decision-making processes. The focus on "decision products" implies a product management approach to analytics and AI solutions.

📈 Primary Responsibilities

• Act as the primary analytical architect and strategic thought partner for the US Asundexian Product Squad, advising Product leadership on critical business decisions.

• Translate high-stakes business questions into comprehensive analytical blueprints, clearly defining the required evidence, data sources, analytical methodologies, Key Performance Indicators (KPIs), and success metrics.

• Design and oversee the end-to-end development of reusable decision products, ensuring they address the Product's most critical needs and deliver tangible business value.

• Conduct sophisticated analyses, including situation analyses, forecasting, launch analytics, performance analytics, and market research such as patient journey mapping, segmentation, and competitive intelligence.

• Collaborate closely with Integrated Decision Products, Data, AI & Product Engineering teams to define data needs, standards, and technical requirements, co-owning product design and prioritization.

• Validate analytical approaches during product development, confirm business fitness, and ensure appropriate release controls before embedding insights into business workflows and enabling user adoption.

• Monitor the performance, quality, and usage of deployed decision products, recommending enhancements, scaling opportunities, or retirement strategies, and resolving recurring issues.

• Promote the reuse of analytical capabilities and decision products across common business needs and workflows to maximize efficiency and impact.

• Lead major analytical deliverables, synthesizing insights from multiple data sources to support strategic planning, commercial execution, and competitive advantage.

📝 Enhancement Note: The responsibilities emphasize a blend of strategic advisory and hands-on analytical leadership. The "decision product" concept suggests a product management approach to analytics, requiring collaboration with engineering and product teams, which is common in advanced analytics and operations roles aiming to operationalize insights.

🎓 Skills & Qualifications

Education:

• Minimum of a Bachelor’s degree in a relevant field.

• Postgraduate degree (Master’s or PhD) in Health Economics, Statistics, Management Science, Business, Marketing, or a related quantitative or business field is preferred. Experience:

• Minimum of 10+ years of relevant work experience in the pharmaceutical or healthcare industry.

• Extensive experience in commercial market intelligence, encompassing primary research, secondary research, third-party data analytics, and vendor management.

• Proven track record of serving as a strategic advisor to senior business leaders and influencing strategic decisions.

• Demonstrated ability to frame complex business decisions and translate them into actionable analytical blueprints, hypotheses, KPIs, and recommendations.

• Experience leading analytical initiatives or products throughout their entire lifecycle, from problem framing and development to deployment, adoption, and continuous improvement.

• Hands-on experience executing complex analyses and facilitating insight generation. Required Skills:

• Deep understanding of the US healthcare environment and its complexities.

• Comprehensive knowledge of key pharmaceutical data sources, including IQVIA, Komodo, Symphony, laptop and iPad detailing data, Specialty Pharmacy data, and formulary data.

• Strong analytical and synthesis skills, with the ability to derive actionable insights from complex datasets.

• Excellent strategic thinking and problem-solving capabilities, with a focus on business impact.

• Proficiency in translating business needs into analytical requirements and data-driven solutions.

• Strong verbal and written communication skills, with demonstrated ability to craft compelling executive presentations, succinct PowerPoint narratives, and clear, actionable recommendations.

• Experience in managing vendor relationships for data and analytics services. Preferred Skills:

• Deep understanding of health system and Integrated Delivery Network (IDN) dynamics.

• Market access analytics experience.

• Familiarity with AI and machine learning concepts as applied to decision-making and product development.

• Experience with data visualization tools and techniques for communicating complex insights.

📝 Enhancement Note: The explicit mention of specific data sources like IQVIA and Komodo is critical for candidates. The emphasis on translating "business decisions into analytical blueprints" and leading "analytical initiatives or products" highlights the need for strong project management and product thinking within an analytics framework.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrations of successfully translating complex business challenges into structured analytical frameworks and actionable insights.

• Case studies showcasing the end-to-end lifecycle management of analytical initiatives or "decision products," from concept to impact.

• Examples of analytical blueprints that clearly defined decisions, users, evidence, data, methods, KPIs, and measures of success.

• Evidence of driving measurable business value and impacting strategic decisions through data analysis and insights.

• Documentation of how insights were embedded into business workflows and led to tangible adoption and action. Process Documentation:

• Showcase expertise in designing and documenting analytical workflows from initial business context to final insight delivery.

• Provide examples of how you've facilitated the validation of analytical approaches and ensured business fitness before deployment.

• Demonstrate experience in monitoring and recommending improvements for analytical product performance, quality, and usage.

• Illustrate how you've promoted the reuse of analytical capabilities and ensured consistency in data standards and methodologies.

📝 Enhancement Note: For this role, a portfolio should highlight not just analytical prowess but also the strategic framing of problems, the design of analytical solutions (blueprints), and the successful implementation and adoption of those solutions as "decision products." Emphasis on ROI and measurable business impact is key.

💵 Compensation & Benefits

Salary Range: $151,120 - $226,680 USD per year.

• Note on Range: This range is provided by the employer and is competitive for a Director-level role in Decision Intelligence/Product Strategy within the pharmaceutical industry in the New Jersey area. Factors such as specific candidate experience, skills, and certifications will influence the final offer.

Benefits:

• Comprehensive Health Care coverage

• Vision benefits

• Dental benefits

• Retirement savings plan

• Paid Time Off (PTO)

• Sick Leave Working Hours:

• Standard full-time hours, likely around 40 hours per week.

• The role involves strategic partnership and delivering insights, which may require flexibility to meet business needs and project deadlines.

📝 Enhancement Note: The salary range is explicitly stated, which is beneficial. The benefits listed are standard but comprehensive for a large pharmaceutical company. The role's strategic nature suggests that while a standard work week is expected, there might be periods of higher intensity to drive critical decisions and product launches.

🎯 Team & Company Context

🏢 Company Culture

Industry: Pharmaceuticals & Life Sciences. Bayer is a global enterprise with core competencies in the life science fields of health care and agriculture. The Pharmaceuticals Division focuses on prescription products, particularly in cardiology, oncology, gynecology, hematology and ophthalmology.

Company Size: Large enterprise (part of Bayer's global presence). This means access to extensive resources, established processes, and a broad network of expertise, but also potentially a more structured and hierarchical environment.

Founded: Bayer was founded in 1863. This long history signifies stability, deep industry knowledge, and a sustained commitment to innovation and research.

Team Structure:

• The role reports to the Senior Director of Decision Intelligence (DI) for Asundexian.

• It is part of the US Asundexian Product Squad, indicating a dedicated, cross-functional team focused on a specific product or therapeutic area.

• Collaboration will be extensive with other groups within DI, including Integrated Decision Products and Data, AI & Product Engineering.

• Expect close partnership with Product leadership and other commercial/strategic functions within the Asundexian business unit. Methodology:

• Data-Driven Decision Making: Core to the DI function, emphasizing the use of data, analytics, and AI to inform and optimize business decisions.

• Integrated Decision Products: A structured approach to developing and deploying analytical capabilities as reusable "products" that integrate seamlessly into business workflows.

• Agile/Iterative Development: Implied through the "full decision-product lifecycle" and "continuous improvement" responsibilities, suggesting an iterative approach to building and refining analytical solutions.

• Strategic Partnership: The role is positioned as a "strategic thought partner," highlighting a consultative approach to engaging with business stakeholders.

Company Website: bayer.com

📝 Enhancement Note: Bayer's reputation as a large, established pharmaceutical company suggests a focus on rigorous scientific validation, regulatory compliance, and a structured approach to innovation. The DI team's focus on "decision products" indicates a modern, product-centric approach to analytics, aiming for scalability and integration.

📈 Career & Growth Analysis

Operations Career Level: Director. This is a senior leadership role, responsible for strategic direction, complex problem-solving, and influencing senior stakeholders. It implies significant autonomy and responsibility for driving outcomes.

Reporting Structure: Reports to a Senior Director within Decision Intelligence, indicating a clear hierarchy within the DI function. The role is embedded within a specific Product Squad (Asundexian), suggesting a focus on delivering value for that particular business unit.

Operations Impact: The role is critical for shaping commercial strategy, optimizing Go-To-Market execution, and driving revenue growth for the Asundexian product. By ensuring data-driven decision-making and embedding insights into workflows, this position directly impacts business performance, competitive positioning, and overall strategic success.

Growth Opportunities:

• Leadership Advancement: Potential to move into Senior Director or VP-level roles within Decision Intelligence, Data Science, or broader Commercial Operations.

• Strategic Influence: Deeper engagement with executive leadership and greater influence on company-wide strategic initiatives.

• Specialization: Opportunity to become a deep subject matter expert in specific therapeutic areas (like Asundexian) or advanced analytical techniques (AI, ML).

• Cross-Functional Mobility: Potential to transition into roles within Product Management, Commercial Strategy, or Business Development, leveraging the strategic and analytical skills developed.

• Learning & Development: Access to Bayer's extensive learning resources, industry conferences, and potential for advanced training in AI and Decision Intelligence.

📝 Enhancement Note: The Director title and reporting structure suggest a significant opportunity for career growth, particularly for individuals looking to lead teams or drive major strategic initiatives within a large pharmaceutical organization. The focus on "decision products" also offers experience in a modern, product-oriented approach to analytics.

🌐 Work Environment

Office Type: Hybrid. While the preferred location is Whippany, NJ, residence-based candidates in the US will be considered, suggesting flexibility. This implies a mix of in-office collaboration and remote work.

Office Location(s): Whippany, New Jersey, United States is the primary location. Bayer has a global presence, but this role is specific to the US operations.

Workspace Context:

• Collaborative Environment: The role requires close collaboration with various teams within DI and the Product Squad, suggesting a dynamic and interactive work setting.

• Data & Technology Focus: Access to sophisticated data platforms, analytical tools, and AI technologies will be essential for executing responsibilities.

• Strategic Engagement: Frequent interaction with senior leadership necessitates a professional and polished communication environment.

• Hybrid Flexibility: The allowance for remote work indicates a modern approach to work-life balance, while still valuing in-person collaboration for strategic discussions and team building.

Work Schedule:

• Standard full-time (likely 40 hours/week).

• Given the strategic nature and focus on decision impact, some flexibility may be required to meet critical business timelines or address urgent analytical needs.

📝 Enhancement Note: The hybrid nature of the role, with remote flexibility for US-based candidates, is a significant factor. This suggests a culture that values productivity and outcomes, while still recognizing the importance of in-person collaboration for strategic alignment and team cohesion.

📄 Application & Portfolio Review Process

Interview Process:

1. Initial Screening: HR or Recruiter screen to assess basic qualifications and alignment with the role.

2. Hiring Manager Interview: Conversation with the Senior Director of Decision Intelligence to delve into experience, strategic thinking, and alignment with DI methodologies.

3. Panel Interviews: Multiple interviews with key stakeholders from the Product Squad, DI team members (analysts, engineers), and potentially Product leadership. These will focus on:

• Analytical Approach: How you frame problems, design analyses, and derive insights.
• Strategic Acumen: Your ability to connect data to business strategy and impact.
• Technical Skills: Proficiency with data sources, analytical methods, and tools.
• Collaboration & Communication: Your ability to work with diverse teams and present complex information clearly.

1. Case Study/Presentation: Candidates may be asked to prepare and present a case study or work through a simulated analytical challenge relevant to the Asundexian product. This will assess your ability to translate a business problem into an analytical blueprint and propose solutions.

2. Final Interviews: Potentially with higher-level leadership to assess overall fit and strategic vision.

Portfolio Review Tips:

• Focus on Impact: Highlight projects where your analytical work led to measurable business outcomes, strategic shifts, or improved decision-making. Quantify results whenever possible (e.g., increased market share, improved campaign ROI, optimized resource allocation).

• Showcase the "Blueprint": Include examples of how you translated vague business questions into clear analytical frameworks, defining hypotheses, data needs, and KPIs.

• Demonstrate Lifecycle Management: Present case studies that illustrate your experience across the full spectrum of analytical initiatives, from initial problem framing and data acquisition to analysis, insight generation, deployment, and ongoing monitoring/improvement.

• Tailor to Bayer: Research Bayer's therapeutic areas, particularly in oncology and cardiology (relevant to Asundexian if it falls within these), and incorporate examples that demonstrate your understanding of the pharmaceutical market and its specific challenges.

• Highlight Collaboration: Show how you partnered with different teams (e.g., commercial, marketing, IT, engineering) to deliver insights and drive adoption.

Challenge Preparation:

• Analytical Problem Solving: Be prepared to discuss how you would approach a hypothetical business problem related to market entry, product performance, patient segmentation, or competitive analysis for a pharmaceutical product.

• Data Interpretation: Practice interpreting complex datasets and explaining your findings and recommendations concisely.

• Strategic Framing: Be ready to articulate how analytical insights can inform high-level business strategy and decision-making.

• AI/ML Application: Understand how AI and machine learning can be applied to enhance decision-making in a commercial pharmaceutical context.

📝 Enhancement Note: The emphasis on "analytical blueprints" and "decision products" indicates that the interview process will likely assess not just technical skills but also the ability to structure complex problems and design systematic solutions. A portfolio showcasing this structured approach will be highly advantageous.

🛠 Tools & Technology Stack

Primary Tools:

• Data Analysis & Synthesis: Advanced analytical techniques, statistical modeling.

• Pharmaceutical Data Platforms: Deep expertise with IQVIA, Komodo, Symphony, Specialty Pharmacy data, formulary data, and potentially others like Veeva or similar CRM/data solutions.

• Business Intelligence & Visualization: Tools like Tableau, Power BI, or similar for creating dashboards and reports to communicate insights.

• AI/ML Platforms: Familiarity with platforms or tools used for developing and deploying AI/ML models, even if not hands-on development, to understand capabilities and collaboration needs.

Analytics & Reporting:

• Proficiency in synthesizing data from disparate sources to generate comprehensive performance reports and situation analyses.

• Ability to design and track KPIs that measure the success of analytical products and their business impact. CRM & Automation:

• Understanding of how analytical insights integrate with CRM systems (e.g., Salesforce, Veeva) to influence sales and marketing actions.

• Familiarity with workflow automation principles to ensure insights are embedded and acted upon efficiently.

📝 Enhancement Note: The explicit mention of specific pharmaceutical data sources (IQVIA, Komodo, Symphony) is a critical requirement. Proficiency in translating complex data into actionable insights for commercial teams is paramount. While not explicitly stated, familiarity with a CRM like Veeva or Salesforce is highly probable given the industry and role focus.

👥 Team Culture & Values

Operations Values:

• Data-Driven Integrity: A commitment to rigorous, unbiased analysis and ensuring data accuracy and reliability in all decision-making processes.

• Strategic Impact: A focus on tackling the most critical business challenges and delivering insights that drive significant strategic value and competitive advantage.

• Collaboration & Partnership: A strong emphasis on working effectively across teams, building trust, and fostering open communication with business stakeholders.

• Continuous Improvement: A dedication to learning, adapting, and refining analytical methodologies, tools, and "decision products" to enhance efficiency and effectiveness.

• Innovation: Embracing new technologies and approaches, including AI and advanced analytics, to solve complex problems in novel ways.

Collaboration Style:

• Consultative and Advisory: Acting as a trusted advisor to Product leadership and commercial teams, providing objective insights and strategic guidance.

• Cross-Functional Integration: Working closely with DI engineering, data science, product management, and commercial functions to ensure alignment and seamless execution of analytical initiatives.

• Proactive Communication: Regularly engaging with stakeholders to understand evolving needs, share progress, and ensure insights are understood and actionable.

• Feedback-Oriented: Open to receiving and providing constructive feedback to continuously improve processes, analyses, and decision products.

📝 Enhancement Note: The emphasis on "Decision Intelligence" suggests a culture that values analytical rigor, strategic foresight, and the operationalization of insights. Collaboration is key, as this role bridges the gap between data science and business strategy.

⚡ Challenges & Growth Opportunities

Challenges:

• Complexity of Pharmaceutical Data: Navigating and integrating diverse, often siloed, pharmaceutical data sources (sales, market, patient, formulary, etc.) to create a holistic view.

• Translating Insights into Action: Ensuring that generated insights are not just reported but are actively adopted and embedded into business workflows and decision-making processes by commercial teams.

• Pace of Innovation: Keeping pace with rapidly evolving AI technologies and analytical methodologies while demonstrating their practical application and ROI in the pharmaceutical context.

• Stakeholder Alignment: Managing diverse stakeholder expectations and priorities across different functions (e.g., commercial, marketing, R&D, IT) to drive consensus on analytical priorities and strategies.

• Measuring Impact: Quantifying the precise business impact and ROI of DI initiatives, especially for complex, long-term strategic decisions.

Learning & Development Opportunities:

• Advanced AI/ML Training: Opportunities to deepen knowledge in cutting-edge AI and machine learning applications relevant to pharmaceuticals.

• Decision Science Expertise: Further development in the principles and practice of decision science and intelligence.

• Therapeutic Area Specialization: Deep dive into the specifics of the Asundexian therapeutic area, gaining expert market knowledge.

• Leadership Development: Participation in Bayer's leadership programs to hone strategic management and team leadership skills.

• Industry Exposure: Attending key industry conferences and forums related to data science, AI, and pharmaceutical commercial strategy.

📝 Enhancement Note: The challenges highlight the need for a candidate who is not only technically proficient but also possesses strong change management, communication, and strategic thinking skills to overcome inertia and drive adoption of data-driven approaches.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you translated a complex business decision into an analytical blueprint. What were the key components of your blueprint, and what was the outcome?" (Assesses ability to frame problems, define requirements, and structure analytical approach.)

• "How would you assess the potential business value of a new decision product for our Asundexian product team? What metrics would you track to demonstrate its impact?" (Evaluates strategic thinking, value assessment, and KPI definition.)

• "Walk me through a situation where you had to synthesize insights from multiple disparate data sources to drive a critical business decision. What were the challenges, and how did you overcome them?" (Tests data synthesis skills and problem-solving in complex data environments.) Company & Culture Questions:

• "Based on your understanding of Bayer and the pharmaceutical industry, what do you see as the biggest opportunities for Decision Intelligence to impact our commercial strategy?" (Assesses research, industry understanding, and strategic alignment.)

• "How do you approach building trust and influencing senior leadership when presenting data-driven recommendations that might challenge existing beliefs or strategies?" (Examines stakeholder management and communication skills.)

• "Describe your experience working within a cross-functional product team. How do you ensure alignment and effective collaboration with diverse functional groups like engineering, product management, and commercial operations?" (Evaluates collaboration style and cross-functional integration.) Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly articulate the business problem, your analytical approach (including the "blueprint"), the data used, the key insights, the recommended actions, and the measurable business impact.

• Quantify Everything: Whenever possible, use numbers and metrics to demonstrate the ROI, efficiency gains, or strategic advantages achieved through your work.

• Visualize Effectively: Use clear, concise visuals (charts, graphs, diagrams) to illustrate your findings and the structure of your analytical solutions. Avoid overly complex or cluttered slides.

• Focus on "Decision Products": Frame your experience in terms of building and delivering analytical solutions that function as reusable "products" for decision-makers.

• Be Prepared for Deep Dives: Anticipate questions about your methodology, data sources, assumptions, and how you would adapt your approach to Bayer's specific context.

📝 Enhancement Note: Candidates should prepare to articulate their process for creating "analytical blueprints" and managing "decision products." Demonstrating a clear, structured approach to problem-solving and impact measurement will be crucial.

📌 Application Steps

To apply for this Director, Decision Intelligence & AI Product Strategy position:

• Submit your application through the Bayer careers portal via the provided URL.

• Tailor your Resume: Emphasize your experience with pharmaceutical market intelligence, strategic advisory roles, translating business needs into analytical blueprints, and managing analytical initiatives across their lifecycle. Use keywords from the job description, such as "Decision Intelligence," "AI," "Product Strategy," "analytical architecture," "KPIs," and specific data sources (IQVIA, Komodo, Symphony).

• Develop Your Portfolio: Prepare 2-3 compelling case studies that showcase your ability to lead complex analytical projects, demonstrate measurable business impact, and illustrate your process for creating "analytical blueprints" and managing "decision products." Focus on pharmaceutical or healthcare examples if possible.

• Practice Your Presentation: Rehearse presenting your portfolio case studies, focusing on clear articulation of the problem, your structured approach, key insights, and quantifiable outcomes. Be ready to discuss how your work directly influenced strategic decisions and revenue generation.

• Research Bayer: Understand Bayer's pharmaceutical portfolio, particularly in areas relevant to Asundexian (e.g., cardiology, oncology), and familiarize yourself with their stated mission and values to articulate your alignment.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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