Associate Dataset Lead

Title: Associate Dataset Lead, PitchBook Data, a Morningstar company
The Team: The PitchBook team performs web-based research and utilizes technology tools to capture hard-to-find data on private capital markets, including private equity (PE), venture capital (VC) and mergers and acquisitions (M&A). This information allows PitchBook's customers such as venture capital firms, private equity firms, limited partners, investment banks, law firms, and accounting firms to discover emerging companies, conduct research on potential investment opportunities, and gain a competitive edge in investment decision-making and negotiations.
The Role: The Associate Dataset Lead (ADL) plays a critical role in improving operational efficiency and driving data-informed decision-making within Primary Operations. This role partners closely with frontline Ops teams, Quality, and Program stakeholders to identify process improvement opportunities, ensure data accuracy and integrity, and support the smooth execution of operational initiatives. The ADL is responsible for analyzing operational performance metrics, surfacing root causes behind performance gaps, and translating insights into clear, actionable recommendations. This role also supports workflow optimization, documentation of SOPs, and continuous improvement efforts across Primary Ops workflows. Success in this role requires a sharp analytical mindset, comfort working with operational data and tooling, strong stakeholder communication, and the ability to thrive in a fast-paced, metrics-driven environment-while proactively identifying opportunities to improve team efficiency, quality outcomes, and overall operational health.
Responsibilities:

• Data Ownership & Subject Expertise
  • Serve as the primary point of contact and subject matter expert for assigned datasets, demonstrating deep knowledge of internal tools, research methodologies and the private markets landscape
  • Leverage PitchBook's in-house tools and business intelligence platforms (e.g., Power BI) to ensure the accuracy, completeness and timeliness of proprietary data
  • Demonstrate expertise in core data domains such as private equity, venture capital, M&A, or institutional investors by researching, collecting, and entering high-quality data into internal systems
• Data Analysis & Reporting

• Collect, analyze, and interpret operational data to identify trends, anomalies, and areas for improvement
  • Develop and maintain dashboards, business reviews, and performance reports for weekly, monthly, and quarterly tracking
  • Prepare regular and ad-hoc reports with actionable insights and clearly articulated recommendations.

• Process Improvement & Operational Excellence
  • Assess existing workflows and collaborate with stakeholders to streamline processes and optimize efficiency.
  • Drive process improvements and methodology updates with documented best practices and standardized implementation plans.
  • Identify root causes of systemic data issues and recommend long-term solutions to improve data quality.
• Cross-Functional Collaboration & Communication
  • Partner with Operations Managers, Dataset Leads, and cross-departmental teams to ensure alignment on priorities, project execution, and data consistency.
  • Facilitate effective communication between teams to provide progress updates, address roadblocks, and celebrate milestones.
  • Support internal knowledge-sharing through detailed documentation, training sessions, and process walk-throughs.
• Compliance, Risk & Quality Assurance
  • Conduct regular audits (process, quality, and policy) to ensure adherence to internal standards and regulatory requirements.
  • Analyze error trends and implement strategies to reduce discrepancies and improve operational accuracy
  • Monitor and mitigate risks such as process gaming and data manipulation while ensuring the integrity of reporting workflows
• Training, Development & Operational Continuity
  • Train and support new team members locally and globally, helping them ramp up quickly on research tools and data methodologies
  • Maintain comprehensive documentation of research processes, tools, and methodologies to support team learning and continuity
  • Assist in recruiting and onboarding efforts, and step in to support broader operational goals during periods of high demand or disruption

Qualifications:

• Undergraduate degree in Economics, Finance, Business or similar, Masters' degree preferred
• 2+ years of experience in operations, business analyst, quality assurance or similar role
• Proficiency in data analysis tools such as Excel, SQL, or BI tools (e.g., Power BI, Tableau) would be a plus
• Ability to thrive under pressure and function effectively in a fast-paced environment under tight deadlines, while working on multiple projects
• Strong analytical and problem-solving skills
• Excellent communication and interpersonal skills
• Ability to work independently and collaboratively

Preferred Qualifications:

• Experience with process improvement methodologies (e.g., Lean, Six Sigma)
• Knowledge of project management principles and tools (e.g., Jira, Asana, Trello)
• Exposure to automation tools or scripting (e.g., Python, AHK, RPA tools)

Morningstar is an equal opportunity employee.
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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