Financial Resource Management Quantitative Analyst
New York, New York, United States
Two Sigma is a financial sciences company, combining data analysis, invention, and rigorous inquiry to help solve the toughest challenges in investment management, insurance technology, securities, private equity, and venture capital.
Our team of scientists, technologists, and academics looks beyond the traditional to develop creative solutions to some of the world’s most complex economic problems.
Our Portfolio Financing team is responsible for the management of our prime brokerage, clearing and executing broker relationships and is part of the larger Financial Resource Management (FRM) group at Two Sigma.
The team is dedicated to developing and enhancing relationships with our financing partners with the goal to optimize services, costs and access across each of the business areas, markets and asset classes in which the company operates. In addition, the team manages the reinvestment of the portfolio's free cash, asset and liability constructs, and counterparty credit risk(s). If you are passionate about joining a fast-paced, dynamic team, we would love to meet you!
You will take on the following responsibilities:
- Utilize existing and new data sources to architect and build a robust centralized financing platform (Whilst not an Engineering role, the candidate is required to operate independently coding and building models and dashboards in Python and Scala)
- Modeling the supply and borrow cost of securities in the securities financing markets
- Simulating, managing and negotiating margin requirements
- Optimizing balances, costs and return profiles of multiple trading entities and counterparties
- Data analytics, creating and improving reports and working with modelers, engineers and portfolio managers to help analyze financing data
- Managing projects such as launching new markets or products for trading
- Leading initiatives that improve and expand how we partner with our brokers
You should possess the following qualifications:
- Applicants should have a strong academic record, at minimum holding a bachelor’s degree with a concentration in Mathematics, Statistics, Computer Science, Engineering, Physics or related.
- Experience or qualifications relating to ‘quantitative finance’ or ‘financial engineering’ highly preferred
- 3-6 years of work experience in Securities Lending, Prime Brokerage or Equity Swap/Portfolio Financing quantitative research from either asset management or investment banking industries.
- Technical scripting ability with either R, Python, Scala or similar language is a prerequisite. Additional basic proficiency with Java, C#, or C++ is required.
- Proven ability to work independently and drive complex, cross-functional projects
- Superior written and verbal communication skills
- Demonstrated success building collaborative working relationships with broad and diverse stakeholder groups
- Strong project management skills. Proven ability to take an idea from blank sheet of paper, to development of clear and concise recommendation, through to execution.
- Understanding of financing structures
- Ability to dive into a wide variety of issues, such as, operations, tax, legal, compliance, risk, general business terms, etc.
You will enjoy the following benefits:
- Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life & disability insurance
- Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms
- Learning: Tuition reimbursement, conference and training sponsorship
- Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves
- Hybrid Work Policy: Flexible in-office days with budget for home office setup
We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.