Position Summary
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.
We are looking for a quantitative researcher with an excellent background in statistical techniques and data analysis to join our Systematic Macro Research team. In this role, you will navigate the full research and trading process and apply a rigorous scientific approach to design sophisticated options and volatility investment models spanning all major global markets.
You Will Take On The Following Responsibilities
- Work closely with other senior leaders to develop, prioritize, and deliver on initiatives within quantitative research
- Help with continued expansion efforts across new regions, asset classes and trading strategies
- Play a key role in all aspects of our cutting-edge systematic investment process, with exposure to workflows including alpha idea generation, statistical analysis, model implementation, portfolio construction, execution and trade analysis
- Use a rigorous scientific method to develop and test sophisticated quantitative investment models and trading strategies
- Contribute to and enhance an options and volatility trading and analytics platform
You Should Possess The Following Qualifications
- At least 5 years of relevant working experience. Familiarity with options and volatility markets along with understanding of derivatives theory and analytics is required.
- Degree in a technical or quantitative discipline like statistics, mathematics, physics, electrical engineering, computer science, or applied economics or finance (all levels welcome, from bachelor’s to doctorate)
- Experience in analyzing large data sets using a modeling language like R or Python
- Ability to formulate semi- and fully-systematic investment hypotheses
- A strong interest in economic fundamentals and market phenomena and the ability to use fundamental and behavioral priors to come up with hypotheses around drivers of factor moves
- Ability to think independently and creatively approach data analysis and communicate complex ideas clearly
- Genuine interest in understanding markets with quantitative tools
- Strong verbal and written communication skills and a collaborative working style
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
The base pay for this role will be between $165,000 and $325,000. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.
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.
Two Sigma is committed to providing reasonable accommodations to qualified individuals in accordance with applicable federal, state, and local laws.
If you believe you need an accommodation, please visit our website for additional information.
