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About the Role
State Street Investment Management's Data, Analytics & AI Services (DAAIS) organization is seeking an experienced Senior Data Product Manager, Vice President to lead the design, development, and delivery of strategic data products and software-enabled business solutions across the investment management enterprise.
This role sits at the intersection of investment management, data, and technology. The successful candidate will partner with stakeholders across the organization to identify opportunities, define product requirements, and translate business needs into scalable data and software solutions that create measurable business value.
The ideal candidate combines deep investment management domain expertise with strong product management and software delivery experience. They are equally comfortable engaging with business leaders, data teams, architects, and software engineers, and have a proven track record of converting complex requirements into actionable product roadmaps and engineering deliverables.
This is not a traditional reporting, analytics, or data governance role. It is a hands-on product leadership position focused on defining, building, and delivering enterprise capabilities that support the evolving needs of a modern investment management organization.
The successful candidate is intellectually curious, self-motivated, and driven to understand both business challenges and technology opportunities. They are comfortable operating in ambiguous environments, asking thoughtful questions, challenging assumptions, and driving initiatives from concept through production delivery.
Key Responsibilities
Product Strategy & Vision
- Define and execute the vision, roadmap, and lifecycle management strategy for strategic data products and software-enabled business capabilities.
- Identify opportunities to improve business processes, decision-making, operational efficiency, and client outcomes through innovative data and technology solutions.
- Partner with stakeholders across investment management functions to understand business objectives, prioritize initiatives, and align product investments with strategic goals.
- Evaluate emerging technologies, industry trends, and market opportunities to inform future product direction.
Requirements & Solution Delivery
- Translate complex business requirements into product specifications, functional designs, user stories, acceptance criteria, and prioritized engineering backlogs.
- Lead product discovery, requirements gathering, feature definition, solution design, implementation planning, testing, deployment, and adoption.
- Decompose large business problems into actionable capabilities and incrementally deliver value through agile methodologies.
- Ensure solutions are scalable, maintainable, and reusable across multiple business functions and use cases.
- Serve as the primary liaison between business stakeholders and engineering teams, ensuring alignment throughout the delivery lifecycle.
Investment Management Data Leadership
- Lead product development efforts across key investment management data domains, including investment, portfolio, product, client, market, reference, operational, distribution, and financial data.
- Define information models, business processes, workflows, data requirements, and operating procedures that support enterprise capabilities.
- Partner with business and technology teams to improve data quality, accessibility, usability, and governance.
- Support strategic initiatives, operating model transformations, business growth objectives, regulatory requirements, and new product launches.
Software & Technology Partnership
- Work closely with architects, engineers, and platform teams to design and deliver modern software-led data solutions.
- Partner in the development of enterprise data platforms, reusable services, APIs, workflows, and intelligent automation capabilities.
- Balance business priorities, delivery timelines, technical complexity, and operational considerations when making product decisions.
- Drive adoption of modern product management and software delivery practices across the organization.
Leadership & Team Development
- Lead and influence cross-functional teams in a matrixed global organization.
- Mentor product managers, analysts, and technology professionals while fostering a culture of ownership, accountability, continuous learning, and execution excellence.
- Build strong partnerships across business, operations, technology, and leadership teams.
- Foster an environment of innovation, collaboration, intellectual curiosity, and continuous improvement.
AI & Emerging Capabilities
- Evaluate and implement AI-enabled solutions that improve productivity, operational efficiency, and business outcomes.
- Partner with engineering teams to leverage modern AI technologies, intelligent workflows, and agentic capabilities where appropriate.
- Identify opportunities to apply structured and unstructured data assets to enhance business decision-making and user experiences.
Required Qualifications
- Bachelor's degree in Finance, Business, Computer Science, Information Systems, Engineering, or a related discipline.
- 15+ years of experience within asset management, investment management, financial services, or financial technology organizations.
- 10+ years of experience in Product Management, Data Product Management, Business Systems, Solution Design, or Software Delivery roles.
- Demonstrated experience delivering enterprise software applications, data platforms, or business technology solutions from concept through production deployment.
- Deep understanding of investment management business processes and operating models.
- Proven experience translating business requirements into software and data solutions.
- Strong experience managing product roadmaps, prioritization, requirements decomposition, backlog management, and delivery execution.
- Experience working directly with software engineering teams in Agile or similar delivery environments.
- Strong analytical and problem-solving skills with the ability to navigate ambiguity and complex business challenges.
- Exceptional written, verbal, and interpersonal communication skills.
- Demonstrated ability to influence stakeholders and drive alignment across business and technology organizations.
- Ability to operate independently while managing multiple initiatives in a fast-paced environment.
Characteristics of a Successful Candidate
The ideal candidate:
- Is intellectually curious and constantly seeks to understand how businesses, data, and technology intersect.
- Is self-motivated and highly accountable, capable of driving initiatives with limited direction.
- Possesses a strong sense of ownership and follows through from concept to production delivery.
- Can comfortably navigate between strategic discussions and detailed execution.
- Enjoys solving complex problems and creating clarity from ambiguity.
- Builds trust and credibility across both business and technology teams.
- Demonstrates sound judgment, pragmatism, and a bias toward action.
- Challenges assumptions constructively and continuously seeks opportunities for improvement.
- Has a passion for building products that create meaningful business impact.
Salary Range:
$120,000 - $217,500 Annual The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ.
Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: our retirement savings plan (401K) with company match; insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages; paid-time off including vacation, sick leave, short term disability, and family care responsibilities; access to our Employee Assistance Program; incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans); and, eligibility for certain tax advantaged savings plans.
For a full overview, visit https://hrportal.ehr.com/statestreet/Home .
About State Street
Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.
We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.
As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.
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Salary Context
This $120K-$217K range is below the median for AI Product Manager roles in our dataset (median: $194K across 123 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At State Street, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills in Demand for This Role
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $220,200 based on 947 positions with disclosed compensation. This role's midpoint ($168K) sits 23% below the category median. Disclosed range: $120K to $217K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
State Street AI Hiring
State Street has 18 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span Cracow, Małopolskie, Poland, Quincy, MA, US, Boston, MA, US. Compensation range: $118K - $217K.
Location Context
AI roles in Boston pay a median of $215,000 across 360 tracked positions.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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