Ledger Analytics Team is Growing
Building a data-informed culture: our world-class Science team.
Exciting times for Ledger Data Science
Ledger is hyper-selective for talents. On the one hand, out of more than 700 résumés per job, on average less than 1 offer is made to candidates. This means de facto less than a 0.15% acceptance rate for applicants. For reference, Harvard’s acceptance rate is 4.92% for the class of 2024.[1]
On the other hand, the Ledger team is now fully remote. Employees can work from home because we firmly believe in hiring the best talents wherever they are, and candidates should live where they please.
“I noticed that the dynamic range between what an average person could accomplish and what the best person could accomplish was 50 or 100 to 1. Given that, you’re well advised to go after the cream of the cream. A small team of A+ players can run circles around a giant team of B and C players.”
Steve Jobs
Our startup mission is to transform the financing structure of the entire insurance industry. Creating new products and the best technologies demands the best talents. What this means for candidates is the ledger admission process can be time-consuming, involves pre-screening, home case study, multiple long call interviews with the team. Many apply but very few are selected for an interview. It takes an exceptional team to accomplish an exceptional mission and often circumstances call for making hard choices.
Scientists to fix insurance
Mark is the Head of Data Science at Ledger. Leading the team that will define the analytics backbone for the emerging trillion-dollar asset class: insurance.
His role is to offer empirical and objective stochastic forecasts of the performance of each risk portfolio we securitize. These forecasts ensure that every participant in the marketplace is at information parity, and are key to determining the market price of each security. He is currently working on a framework to generate these forecasts in an automated fashion at scale on a wide variety of input data across multiple lines of business.
We are proud to announce that Tom and Bill are joining the Ledger Data Science team.
Tom is responsible for developing and scaling Ledger’s risk modeling capabilities and the data infrastructure needed to support them. He has years’ analytical experience in the industry, including in actuarial roles in both pricing and reserving. Before Ledger, he was a senior actuarial analyst at Allianz Life, responsible for enforcing rate-setting and leading technical initiatives in financial modeling, data engineering, and predictive analytics.
Bill is a data scientist and software developer with experience in probabilistic programming, cybersecurity data analysis, and the power industry.
He studied Physics at the University of Oregon and Stats at Portland State University. He strongly enjoys long random walks on the beach. Despite being discrete, he is continuously learning.
It takes an exceptional team
Guiding principles at Ledger are inspired by Y Combinator and the Sequoia Capital’s Data Science team.[2]
Smart hiring of top-tier talent implies promoting a culture of ownership and transparency. Ledger heavily supports its talents as the company’s future leaders and product designers. The startup sets standards of excellence and prioritize so that every person has a measurable impact on company goals.
We are building technologies that power insurance innovation, promoting the new standard in insurance financing.
Ledger Investing is looking for world-class skills and experience to drive a new $1 Trillion asset class. So if you’ve got the know-how, drive, and humility to improve every day, we’d love to hear from you.
Visit us at https://ledgerinvesting.com/
