Quantitative Research Analyst

At Pitch Book, a Morningstar company, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We're deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company.

Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there's going to be some ambiguity along the way, but we excel when we challenge ourselves. We're willing to take risks, fail fast, and do it all over again in the pursuit of excellence.

If you have a good attitude and are willing to roll up your sleeves to get things done, Pitch Book is the place for you.

Pitch Book Institutional Research Group is a provider of research services to private market investors, advisors and market participants. The group provides Investment strategy, fund performance, and industry research through a differentiated, framework-driven approach. In addition, the group provides custom research and data analysis support to subscribing clients. The Quantitative Research team sits within the broader group and builds proprietary models, indexes, and analytical tools and publishes research that explains them.

The team works closely with our Product, Engineering, and Data Operations Groups to take these models and tools from prototype to production, solving our clients' problems and empowering their workflows.

Pitch Book's Institutional Research Group is looking to hire a Quantitative Research Analyst to join our Seattle-based research function. This role sits at the intersection of research and data science: you will design and build statistical and machine learning models on top of Pitch Book's proprietary datasets, work cross-functionally to deliver the resulting tools to clients, and author research that explains the methodology and its implications for private markets.

You will work end-to-end, from data exploration and model prototyping through validation, productionization, and go-to-market delivery. The research, model, and tools this team produces are utilized by many of the largest and most influential private capital investors, asset managers, investment banks, and service providers globally. Our team is analytical, technically rigorous, entrepreneurial, and focused on turning proprietary data into differentiated products and insights for our clients.

• Design, build, and validate statistical and machine learning models and methodologies on top of Pitch Book's proprietary datasets
• Support the full lifecycle of analytical tools and models, partnering across teams to deliver insights to clients
• Write and publish research that explains the methodology, findings, and market implications of the team's models and analysis for a range of institutional readers
• Work closely with other quant research analysts to develop new models and metrics, as well as identify unique data points to support research and tools
• Serve as market experts and maintain a deep understanding of the market environment and how it impacts our clients' workflows and needs
• Manage and complete select time-sensitive requests and inquiries fabout the team's models, methodologies, and research from clients, press, internal colleagues, and the general public
• Support the vision and values of the company through role modeling and encouraging desired behaviors
• Participate in various company initiatives and projects as requested

• Bachelor's degree in a quantitative field;
  Including finance, economics, statistics, computer science, data science, or mathematics
• 3+ years of experience 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

• Strong understanding of financial concepts such as valuation techniques (discounted cash flow modeling, comps, etc.), Internal Rate of Return, asset allocation and more
• Experi…