Quantitative Researcher: ML Models for Private Markets

PitchBook Data; Seattle (WA); On-site; USD 120,000 - 140,000; Full time

Benefits offered by this job

Annual bonus

Educational stipend

Paid time off

In-office collaboration

Job summary

PitchBook Data, a Morningstar company, is seeking a Quantitative Research Analyst to design and build statistical and ML models atop PitchBook’s proprietary datasets. You will work end-to-end from exploration to production, collaborating with product, engineering, and data operations to deliver tools used by major investors and financial institutions.

The role emphasizes rigorous experimentation, cross-functional collaboration, and clear communication of research findings.

Qualifications

• Bachelor’s degree in a quantitative field (finance, economics, statistics, computer science, data science, or mathematics).
• 3+ years in a quantitative research, data science, or ML engineering role.
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future.

Responsibilities

• Design, build, and validate statistical and machine learning models on PitchBook’s proprietary datasets.
• Support the full lifecycle of analytical tools and models, partnering across teams to deliver insights to clients.
• Write and publish research explaining methodology, findings, and market implications for institutional readers.
• Collaborate with other quant research analysts to develop new models and metrics.
• Stay updated on market conditions to ensure models remain relevant to clients’ workflows.

Skills

Python programming

Machine learning

Data analysis

Statistical modeling

Communication skills

Education

Bachelor’s degree in a quantitative field

Tools

Python

SQL

Pandas

scikit-learn

PyTorch

Job description

PitchBook Data, a Morningstar company, is seeking a Quantitative Research Analyst to design and build statistical and ML models atop PitchBook’s proprietary datasets. You will work end-to-end from exploration to production, collaborating with product, engineering, and data operations to deliver tools used by major investors and financial institutions.

The role emphasizes rigorous experimentation, cross-functional collaboration, and clear communication of research findings.