IR Product Strategy Lead (AI and Data)

📍 Job Overview

Job Title: IR Product Strategy Lead (AI and Data)

Company: Nasdaq

Location: London, United Kingdom

Job Type: Full time

Category: Product Management / Revenue Operations Enablement

Date Posted: September 3, 2026

Experience Level: 5-10 years

Remote Status: Hybrid

🚀 Role Summary

• Define and drive the product strategy for AI-powered intelligence products within Nasdaq's IR Intelligence division, ensuring alignment with business objectives and evolving market needs.

• Lead end-to-end product delivery, from user research and proof-of-concept through to release, ensuring quality, documentation, and user adoption.

• Partner with UX designers and engineering teams to design intuitive, AI-first solutions that address real user needs at scale, leveraging data insights for product enhancement.

• Prioritize and manage the product backlog, balancing technical feasibility, business value, and user impact to optimize GTM strategies.

• Build strong relationships with clients, internal stakeholders, and cross-functional teams to gather insights, champion AI adoption, and drive successful outcomes.

📝 Enhancement Note: This role, while titled "Product Strategy Lead," has significant overlap with Revenue Operations and GTM enablement functions. The focus on AI-driven insights, client-facing products, and driving adoption directly impacts sales effectiveness, customer success, and ultimately, revenue generation. The emphasis on data solutions and translating complex requirements into actionable product strategies is a core competency for operations leaders aiming to drive GTM efficiency and effectiveness.

📈 Primary Responsibilities

• Product Vision & Strategy: Develop and articulate a clear product vision for AI-driven intelligence products, translating market trends and client needs into a robust, data-informed product roadmap that supports GTM objectives.

• End-to-End Product Delivery: Manage the entire product lifecycle, from ideation and user research to development, testing, launch, and post-launch iteration, ensuring successful product adoption and market fit.

• Cross-Functional Collaboration: Act as a liaison between engineering, UX design, sales, marketing, and client success teams to ensure product development aligns with user needs and business goals, fostering a cohesive GTM approach.

• Backlog Management & Prioritization: Own and meticulously manage the product backlog, using data-driven prioritization frameworks to balance feature development, technical debt, and strategic initiatives that enhance revenue generation capabilities.

• Client & Stakeholder Engagement: Proactively engage with clients and internal stakeholders to gather feedback, identify pain points, and champion the adoption of AI-powered solutions, ensuring products deliver tangible business value and support sales efforts.

• AI/ML Integration: Work closely with AI/ML teams to integrate advanced capabilities into client-facing products, ensuring these features are user-friendly and drive measurable improvements in client workflows and decision-making.

• Market Analysis & Competitive Intelligence: Continuously monitor market trends, competitive landscapes, and emerging AI technologies to identify opportunities for product innovation and differentiation within the financial technology sector.

📝 Enhancement Note: The responsibilities highlight a strong need for strategic thinking, execution capability, and cross-functional influence, all critical for effective GTM operations. The ability to translate complex AI/data capabilities into user-friendly products that drive adoption is directly linked to revenue enablement.

🎓 Skills & Qualifications

Education: Bachelor's degree in a relevant field (e.g., Computer Science, Engineering, Business, Finance) or equivalent practical experience.

Experience: 5-10 years of proven experience in agile product management, with a strong emphasis on B2B enterprise SaaS and financial markets. Demonstrated track record of successfully delivering AI and data solutions to end-users.

Required Skills:

• Product Strategy Development: Ability to define and drive product strategy, vision, and roadmaps for complex B2B SaaS products.

• Agile Product Management: Deep understanding and practical experience with agile methodologies (Scrum, Kanban) for iterative product development and delivery.

• AI/Data Product Delivery: Proven experience in delivering AI and data-driven solutions, understanding the nuances of data integration, model deployment, and user adoption.

• User Research & Requirements Gathering: Proficiency in conducting user research, synthesizing feedback, and translating complex user needs into clear product requirements and user stories.

• Cross-Functional Leadership: Ability to collaborate effectively with engineering, design, marketing, sales, and client success teams in a global, matrixed environment.

• Communication & Presentation: Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to diverse audiences, including executive stakeholders.

• Backlog Management: Expertise in prioritizing and managing product backlogs to maximize business value and user impact.

Preferred Skills:

• Financial Markets Data: Experience with financial markets data, client-facing data products, or workflow solutions within the financial technology sector.

• AI/ML Concepts: Familiarity with AI/ML concepts, integration patterns, and best practices within enterprise product development.

• Global Stakeholder Engagement: Experience working with and influencing global teams and managing cross-border stakeholder relationships.

• UX/UI Collaboration: Ability to partner effectively with UX designers to create intuitive and user-centric product interfaces.

• SaaS Operations: Understanding of SaaS business models, customer success, and GTM operations.

📝 Enhancement Note: The preferred qualifications underscore the importance of domain expertise in financial markets and a solid grasp of AI/ML, which are increasingly critical for operations roles focused on leveraging advanced technologies for GTM efficiency.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Product Strategy Case Studies: Showcase examples of defining and executing product strategies for B2B SaaS products, highlighting the process from market analysis to roadmap development.

• AI/Data Product Deliverables: Present evidence of successfully launching AI or data-driven products, detailing the user research, feature prioritization, and go-to-market (GTM) execution.

• Agile Process Documentation: Include artifacts demonstrating proficiency in agile workflows, such as prioritized backlogs, user stories, sprint reviews, and retrospectives.

• Cross-Functional Collaboration Examples: Provide examples of how you've successfully partnered with engineering, design, sales, and marketing to bring products to market, emphasizing communication and alignment strategies.

Process Documentation:

• Workflow Design & Optimization: Demonstrate experience in designing and optimizing complex workflows, particularly those involving data integration and AI-driven insights, to improve operational efficiency.

• Product Launch & Adoption Strategies: Document successful product launch plans and strategies implemented to drive user adoption and ensure client success, with measurable outcomes.

• Data-Driven Decision Making: Illustrate how data analytics and user feedback were used to inform product decisions, prioritize features, and iterate on product development for continuous improvement.

📝 Enhancement Note: A strong portfolio for this role will emphasize not just product features, but the strategic thinking, process rigor, and cross-functional collaboration required to bring AI-driven solutions to market and ensure their successful adoption, which directly impacts GTM and revenue operations.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for a Product Strategy Lead with 5-10 years of experience in London, the estimated annual salary range is £80,000 - £120,000. This estimate considers factors such as the seniority of the role, the specific demands of AI and data product strategy in the financial technology sector, and the cost of living in London.

Benefits:

• Competitive base salary

• Annual bonus

• Annual equity grant

• Employee Stock Purchase Plan offering discounted company shares

• Pension matching

• 28 paid vacation days

• 6 additional days off per year

• Work from (almost) anywhere – up to 20 days/year

• Paid time off to volunteer

• Health insurance

• Dental insurance

• Gym allowance

• 24/7 mental health support for you and your family

• Global mentoring program

• Unlimited access to e-learning platforms

• Hybrid work setup

Working Hours: Standard full-time hours, likely around 40 hours per week, with flexibility expected to meet project deadlines and collaborate effectively across global time zones.

📝 Enhancement Note: The estimated salary range is based on research of similar Product Lead roles in London within the FinTech sector, considering the AI and data specialization. The provided benefits are comprehensive and align with typical offerings for senior roles at established financial technology firms, supporting employee well-being and professional development.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Technology (FinTech) and Capital Markets. Nasdaq is a global leader in providing critical market infrastructure, data, and technology solutions to the financial industry. This context means a fast-paced, highly regulated, and data-intensive environment.

Company Size: Nasdaq is a large, publicly traded corporation with thousands of employees globally. This scale implies structured processes, extensive resources, and opportunities for significant impact, but also requires navigating a complex organizational structure.

Founded: Nasdaq was founded in 1971, bringing decades of experience and a deep understanding of market dynamics and technological evolution. This history suggests a culture that values innovation grounded in established expertise.

Team Structure:

• The role reports to James Tickner, likely a Director or VP within the IR Intelligence division.

• The Product team is expected to be highly collaborative, working closely with dedicated Engineering, UX Design, and Data Science/AI teams.

• Significant interaction with Sales, Client Success, Marketing, and potentially Legal/Compliance teams is anticipated, given the nature of financial products and B2B client engagement. Methodology:

• Data-Driven Product Development: Expect a strong emphasis on using data analytics, user feedback, and market intelligence to inform product strategy, prioritize features, and measure success.

• Agile & Lean Principles: The product development lifecycle likely adheres to agile methodologies, focusing on iterative delivery, continuous improvement, and rapid response to market changes.

• Client-Centric Innovation: A core focus will be on understanding and solving real-world client problems within the Investor Relations (IR) and financial markets space, using AI and data to provide actionable intelligence.

Company Website: https://www.nasdaq.com/

📝 Enhancement Note: Nasdaq's position as a major player in FinTech suggests a culture that values precision, compliance, and innovation. For operations professionals, this means a focus on robust processes, data integrity, and delivering solutions that directly impact financial market efficiency and client success. The emphasis on AI and data points to a forward-thinking approach within a historically established organization.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a Lead, indicating a senior individual contributor or potential team lead capacity within the product management function. It requires strategic thinking, end-to-end product ownership, and significant influence across departments. For operations professionals, this role offers a unique opportunity to bridge the gap between product development and GTM execution, driving revenue enablement through intelligent product solutions.

Reporting Structure: The role reports to James Tickner, likely a senior leader within the IR Intelligence division. This implies mentorship opportunities and exposure to executive-level strategic discussions. The lead will also need to influence peers and direct reports (if any) within engineering, design, and GTM teams.

Operations Impact: The IR Product Strategy Lead's work directly impacts Nasdaq's ability to provide cutting-edge AI-driven intelligence to its clients. Successful product strategy and delivery translate into enhanced client value, improved sales conversations, increased customer retention, and ultimately, direct contributions to revenue growth and market share expansion for Nasdaq's IR Intelligence offerings.

Growth Opportunities:

• Strategic Product Leadership: Opportunity to shape the future of AI and data products in the IR space, with potential to grow into a Director or VP of Product role.

• Domain Expertise Development: Deepen expertise in financial markets, investor relations, and cutting-edge AI/ML applications within enterprise software.

• Cross-Functional Influence: Develop strong leadership and influencing skills by working across diverse global teams (engineering, sales, marketing, client success).

• Mentorship & Skill Development: Access to Nasdaq's global mentoring program and unlimited e-learning platforms for continuous skill enhancement in product management, AI, and financial technology.

📝 Enhancement Note: This role is a significant step for professionals looking to deepen their impact on revenue generation through product strategy, especially in the AI and data domain. The growth trajectory suggests a path toward broader leadership within product or GTM operations.

🌐 Work Environment

Office Type: The role is based in London, Bishopsgate, and operates on a hybrid model, requiring at least 3 days per week in the office. This suggests a modern office environment designed to facilitate collaboration, innovation, and team connection.

Office Location(s): London - Bishopsgate, United Kingdom. This prime London location offers excellent accessibility via public transport and places the employee within a vibrant business district.

Workspace Context:

• Collaborative Hub: The office environment is expected to be a hub for cross-functional collaboration, team meetings, brainstorming sessions, and client interactions.

• Technology-Enabled: Access to Nasdaq's robust technology infrastructure, including necessary software, hardware, and connectivity to support product development and communication.

• Team Interaction: Regular opportunities for in-person interaction with immediate team members (engineering, UX, data science) and other stakeholders, fostering strong working relationships.

Work Schedule: While a standard 40-hour work week is implied, the hybrid nature and global reach of Nasdaq may require flexibility. The role demands proactive time management to balance in-office collaboration with focused, remote work for deep product strategy and analysis.

📝 Enhancement Note: The hybrid work environment balances the need for in-person collaboration, essential for product strategy and team cohesion, with the flexibility valued by modern professionals. The London location offers a dynamic professional ecosystem.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review applications and conduct an initial screening call to assess basic qualifications and cultural fit.

• Hiring Manager Interview: A detailed discussion with James Tickner, focusing on product strategy experience, AI/data product knowledge, and leadership capabilities. Be prepared to discuss your approach to product vision, roadmap development, and cross-functional collaboration.

• Panel Interview: Likely involves interviews with key stakeholders from engineering, UX, and GTM teams. Expect questions on agile methodologies, backlog prioritization, client engagement, and your understanding of the financial markets.

• Product Case Study/Presentation: A common step for product roles. You may be asked to present a case study on a past product success, analyze a hypothetical product challenge, or outline a strategy for an AI-driven IR product. This is where your portfolio will be crucial.

• Final Round: May involve senior leadership for a final assessment of strategic alignment and cultural fit.

Portfolio Review Tips:

• Focus on Impact: For each project, clearly articulate the problem you solved, the solution you developed, your specific role, and the measurable business impact (e.g., revenue growth, client adoption, efficiency gains).

• Showcase AI/Data Expertise: Highlight projects where you leveraged AI or data to drive product innovation and deliver actionable insights. Explain your thought process in integrating these technologies.

• Demonstrate Process Rigor: Include examples of your agile practices, backlog management techniques, and cross-functional collaboration strategies. Visual aids like roadmaps, wireframes, or process diagrams can be effective.

• Tailor to Nasdaq: Research Nasdaq's IR Intelligence products and target audience. Frame your portfolio examples to demonstrate how your skills and experience align with their strategic goals and market position.

• Keep it Concise: Aim for 3-5 strong, relevant case studies that clearly illustrate your core competencies.

Challenge Preparation:

• Product Strategy & Vision: Be ready to discuss how you develop product strategies, identify market opportunities, and set a clear vision for AI-driven products.

• Agile & Prioritization: Prepare to explain your approach to backlog management, sprint planning, and prioritizing features based on business value and user impact.

• AI/Data Integration: Think through how you would approach integrating AI/ML into an enterprise SaaS product, considering technical feasibility, user experience, and ethical implications.

• Stakeholder Management: Prepare examples of how you have managed complex stakeholder relationships and driven consensus across different departments.

📝 Enhancement Note: The interview process is designed to assess not just technical product skills but also strategic thinking, leadership potential, and the ability to operate effectively within a large, global organization. A well-curated portfolio is essential for showcasing practical experience and impact.

🛠 Tools & Technology Stack

Primary Tools:

• Product Management Platforms: Jira, Confluence, Asana, or similar tools for backlog management, sprint tracking, and documentation.

• Prototyping & Design Tools: Figma, Sketch, Adobe XD for collaborating with UX designers on user interfaces and workflows.

• Data Analysis & Visualization: Tools like Tableau, Power BI, Looker, or SQL for analyzing product usage data, client behavior, and market trends.

• CRM Systems: Salesforce or similar for understanding client needs, sales processes, and customer lifecycle management.

Analytics & Reporting:

• Product Analytics: Amplitude, Mixpanel, or similar for tracking user engagement, feature adoption, and conversion funnels.

• Business Intelligence (BI) Tools: For generating reports on product performance, market share, and revenue impact.

• A/B Testing Platforms: For experimenting with product features and optimizing user experiences.

CRM & Automation:

• CRM: Salesforce (likely used by Sales and Client Success teams, requiring collaboration).

• Marketing Automation: HubSpot, Marketo (for understanding GTM activities and client communication strategies).

• Integration Tools: Understanding of how different systems (CRM, BI, product platforms) integrate to provide a unified view of client and product data.

📝 Enhancement Note: Proficiency with a range of product management, analytics, and collaboration tools is expected. The ability to leverage these tools to drive data-informed decisions and optimize GTM processes is critical for this role.

👥 Team Culture & Values

Operations Values:

• Data-Driven Decision Making: A strong emphasis on using data and analytics to inform all product decisions, from strategy setting to feature prioritization. Operations professionals are expected to champion a data-first approach.

• Client-Centricity: A commitment to understanding and solving client problems, ensuring that products deliver tangible value and support client success, which directly impacts retention and revenue.

• Collaboration & Transparency: Fostering an environment of open communication and teamwork across departments (Product, Engineering, Sales, Marketing, Client Success) to ensure alignment and shared success.

• Innovation & Adaptability: Encouraging the exploration of new technologies, particularly AI and ML, and maintaining agility to adapt to evolving market demands and client needs.

• Excellence & Accountability: A drive for high-quality execution, meticulous attention to detail, and taking ownership of product outcomes and their impact on the business.

Collaboration Style:

• Cross-Functional Integration: Expect a highly collaborative environment where Product, Engineering, UX, Sales, and Marketing teams work in lockstep to define, build, and launch products.

• Feedback-Rich Environment: A culture that encourages constructive feedback and open dialogue to continuously improve products and processes.

• Knowledge Sharing: Opportunities for sharing insights, best practices, and lessons learned across teams, particularly concerning AI/data applications and GTM strategies.

📝 Enhancement Note: Nasdaq's culture likely values professionalism, expertise, and a results-oriented approach. For operations roles, this translates to a focus on process, data integrity, and measurable impact on revenue and client success.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating a Large Organization: Adapting to the processes, communication channels, and stakeholder dynamics within a large, global corporation like Nasdaq.

• Rapidly Evolving AI Landscape: Staying abreast of cutting-edge AI advancements and effectively integrating them into enterprise products while managing technical complexity and user adoption.

• Balancing Stakeholder Needs: Effectively managing competing priorities and feedback from diverse stakeholders (clients, sales, engineering, leadership) to drive a cohesive product strategy.

• Data Complexity in Finance: Working with complex, often sensitive, financial market data, requiring a deep understanding of data governance, accuracy, and regulatory compliance.

Learning & Development Opportunities:

• Advanced AI/ML Training: Access to e-learning platforms and potential for specialized training in AI/ML applications within finance.

• Product Leadership Skills: Opportunities to develop strategic leadership, stakeholder management, and executive communication skills through mentorship and challenging projects.

• Financial Markets Expertise: Deepen knowledge of investor relations, capital markets, and financial technology through direct exposure and company resources.

• Global Collaboration Experience: Gain valuable experience working with diverse international teams, enhancing cross-cultural communication and project management skills.

📝 Enhancement Note: This role offers significant opportunities for growth by tackling complex challenges in a dynamic industry, leveraging advanced technologies, and developing leadership capabilities within a respected global organization.

💡 Interview Preparation

Strategy Questions:

• "Describe your process for defining a product strategy for a new AI-driven feature. How would you validate its potential market impact and align it with GTM goals?" (Focus on market analysis, user research, roadmap integration, and revenue potential.)

• "How do you prioritize features in a product backlog when faced with competing demands from sales, engineering, and client success? Walk us through a framework you've used." (Emphasize data-driven prioritization, ROI calculation, and stakeholder alignment.)

• "Imagine we want to integrate a new AI capability to provide predictive insights for investor relations. What are the key steps you would take to define, develop, and launch this product?" (Focus on user needs, technical feasibility, data requirements, GTM strategy, and adoption plans.) Company & Culture Questions:

• "What interests you specifically about Nasdaq and our IR Intelligence division, particularly in the context of AI and data?" (Research Nasdaq's mission, products, and recent AI initiatives.)

• "How do you approach collaboration with engineering and UX teams to ensure AI products are both technically sound and user-friendly?" (Highlight your experience in cross-functional partnerships and user-centric design.)

• "How do you measure the success of a product, especially one leveraging AI? What KPIs would you track for an IR Intelligence product?" (Focus on adoption rates, client satisfaction, ROI, and impact on GTM metrics.) Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly define the problem, your solution, your role, the process followed, and the quantifiable results. Use a STAR (Situation, Task, Action, Result) method.

• Highlight AI/Data Impact: Emphasize how AI and data were instrumental in driving the product's success and delivering value. Quantify the impact wherever possible.

• Showcase Process & Collaboration: Detail your involvement in agile processes, backlog management, and how you collaborated with different teams to achieve outcomes.

• Be Ready for Deep Dives: Anticipate detailed questions about your decision-making process, technical challenges, and how you handled trade-offs.

📝 Enhancement Note: Preparation should focus on demonstrating strategic thinking, a deep understanding of AI/data product management, and the ability to translate technical capabilities into business value that supports revenue operations and GTM success.

📌 Application Steps

To apply for this IR Product Strategy Lead position at Nasdaq:

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

• Tailor Your Resume: Customize your resume to highlight experience in B2B SaaS, AI/Data product management, agile methodologies, and financial markets. Quantify achievements with specific metrics related to product success and GTM impact.

• Prepare Your Portfolio: Curate 3-5 strong case studies that showcase your product strategy, AI/data product delivery, and cross-functional collaboration skills. Focus on demonstrating quantifiable results and your strategic approach.

• Research Nasdaq: Familiarize yourself with Nasdaq's IR Intelligence offerings, their market position, and recent company news, particularly related to AI and data initiatives.

• Practice Interview Responses: Prepare for common product management, AI/data, and strategy questions. Rehearse your portfolio presentation to ensure a clear, concise, and impactful delivery.

⚠️ 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.