Job Description

PitchBook’s Associate Product Manager works collaboratively with key Product stakeholders and teams to deliver the department’s product roadmap. This role takes an active part in aligning our engineering activities with Product Objectives across new product capabilties as well as data and scaling improvements to our core technologies, with a focus on AI/ML data extraction, enrichment, and collection capabilities.

Team Overview

The Data Product team within PitchBook’s Product organization develops solutions to support and accelerate our data operations processes. This domain impacts core workflows of data capture, ingestion, and hygiene across our core private and public capital markets datasets. This role works with our AI/ML Collections Data Extraction & Enrichment teams, closely integrated with Engineering and Product Management to ensure we are delivering against our Product Roadmap. These teams provide backend AI/ML services that power PitchBook’s data collection activities and related internal content management systems.

Outline of Duties and Responsibilities

• Be a domain expert for your product areas and understand user workflows and needs
• Actively define backlog priority for your teams in collaboration with Product and Engineering
• Manage delivery of features according to the Product Roadmap
• Validate the priority and impact of incoming requirements from Product Management and Engineering
• Break down prioritized requirements into well-structured backlog items for the engineering team to complete
• Create user stories and acceptance criteria that indicate successful implementation of requirements
• Communicate requirements, acceptance criteria, and technical details to stakeholders across multiple PitchBook departments
• Define, create, and manage metrics that represent deliverable impact
• Manage, track, and mitigate risks or blockers of Feature delivery
• Support execution of AI/ML collections work related but not limited to AI/ML data extraction, collection, and enrichment services
• Support PitchBook’s values and vision
• Participate in various company initiatives and projects as requested

Experience, Skills and Qualifications

• Bachelor's degree in Information Systems, Engineering, Data Science, Business Administration, or a related field
• 3+ years of experience in a Product role within AI/ML or enterprise SaaS domains
• A proven record of shipping high impact data pipeline or data collection-related tools and services
• Familiarity with AI/ML workflows, especially within model development, data pipelines, or classification systems
• Experience collaborating with globally distributed product engineering and operations teams across time zones
• Excellent communication skills to drive clarity and alignment between business stakeholders and technical teams
• Bias for action and a willingness to roll up your sleeves and do what is necessary to meet team goals
• Experience translating user-centric requirements and specifications into user stories and acceptance criteria
• Superior attention to detail including the ability to manage multiple projects simultaneously
• Strong verbal and written communication skills, including strong audience awareness
• Experience with shared SDLC and workspace tools like JIRA, Confluence, and data reporting platforms

Preferred Qualifications

• Direct experience with applied AI/ML Engineering services. Strong understanding of supervised and unsupervised ML models, including their training data needs, evaluation frameworks, and lifecycle impacts
• Background in fintech supporting content sourcing, collection, management, and engineering implementation
• Experience with data quality measurements, annotation systems, knowledge graphs, and ML Model evaluation
• Exposure to cloud –based ML infrastructure and data pipeline orchestration tools such as AWS SageMaker, GCP Vertex AI, Airflow, and dbt
• Certifications related to Agile Product Ownership / Product Management such as CSPO, PSPO, POPM are a plus

Working Conditions

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. This role collaborates with Seattle and New York-based stakeholders, and typical overlap is between 7:00 – 8:30AM Pacific. Limited corporate travel may be required to remote offices or other business meetings and events.

Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.

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