About Ledger Investing
Ledger Investing is a Y Combinator backed insure-tech startup that is transforming the way insurance risks are financed. Today, Ledger is an online marketplace connecting insurance risk to capital, focusing on securitization. Insurance risk originators are able to source capital more efficiently vs. the traditional value-chain. Capital providers gain access to an asset class that is highly diversified vs. most asset classes. Insurance securitization has quickly grown to be a $100 billion market but is limited in scope due to opacity and complexity. Ledger is expanding this market to $1 trillion by building a seamless data pipeline from the policyholder to the capital markets, enabling transparency, and bringing best-in-class analytics and real-time insights to the table. Our recent $75 million Series B round of investment funding has set us up for exponential growth. We are on our way to disrupting the industry by serving as an unparalleled, advantageous marketplace for virtually all types of insurance risks and capital, including traditional reinsurers, institutional investors, and accredited investors.
About the Position:
At Ledger Investing, we are building a market for a new class of financial assets that will have transformative impacts on casualty insurance, reinsurance, and institutional investors alike. These financial assets are fairly complex and involve expertise across multiple domains.
This posting is for a unique position within the Ledger organization. You will be a member of the Data Science team, as such, you will have regular opportunities to interact with other data scientists and contribute to analytical work at the company. However, the majority of your time will be spent working directly with the company’s CEO and Chief Data Scientist on special projects.
Many of the special projects will focus on demystifying what we do for the sake of both insurers and investors. We are particularly interested in building software tools that help clearly explain the nature of insurance risk, insurance market dynamics, the financial structure of insurance-linked securities, and other such topics. These tools will educate and empower the insurance and investing communities to better understand these novel assets.
About You:
Successful candidates will have all of the following attributes:
- Strong skills in Python programming, including familiarity with the NumPy and SciPy libraries.
- Demonstrated skills in translating high-level concepts and ideas into concrete, precise, and technically rigorous implementations.
- Solid grasp of the principles of data visualization and ability to generate rich and insightful plots of quantitative data.
- Experience with quantitative finance, including financial modeling.
- Ability to communicate complex technical ideas to non-technical audiences.
- Strong attention to detail and ability to work independently.
The following attributes will help candidates stand out from the crowd:
- A graduate degree in finance, statistics, operations research, or another applied quantitative field.
- Knowledge of the property & casualty insurance industry.
- Familiarity with version control, especially Git/GitHub.
- Experience with simulation-based modeling and/or operations research.
Your Benefits:
- Competitive salary, bonus potential, and equity compensation
- Work from anywhere. We’re flexible. Our headquarters is in New York, but this position can be fully remote or hybrid.
- Uncapped paid time off
- Paid Holidays
- 401k
- Medical, dental, and vision insurance - multiple plans to choose from
- Company paid Life and AD&D insurance
- ClassPass - We contribute to your monthly membership offering a large range of providers & services in Fitness and Wellness. Get a massage on us!
- Up to $5,000 paid by Ledger towards your dream desk setup! Customize what works for you.
For US based positions:
Ledger Investing is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. We strictly prohibit and do not tolerate discrimination against employees, applicants, or any other covered persons because of race, color, religion, creed, national origin or ancestry, ethnicity, sex, gender (including gender nonconformity and status as a transgender or transsexual individual), sexual orientation, marital status, age, physical or mental disability, citizenship, past, current or prospective service in the uniformed services, predisposing genetic characteristic, domestic violence victim status, arrest records, or any other characteristic protected under applicable federal, state or local law.
