Quantitative Researcher/Modeler: Equities

Key Skills

C Programming, C++, Cloud computing, Data science techniques, Java Programming, Machine learning techniques, MATLAB Programming, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

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 seeking a self-motivated Quantitative Researcher to join a team within our Equities division. This quantitative modeler will develop systematic signals to generate alpha and increase capacity, partnering closely with other domain experts across modelling, portfolio management, platform and trading to drive successful implementation of new strategies.

You will take on the following responsibilities:

• Primary responsibility is to generate new alpha through quantitative, event-driven signals related to both ETF- and index- trading.
• Ability to gather, maintain and analyze economic and financial data in support of global ETFs and indices. Expertise with large panel datasets of market micro-structure data, including intra-day quote and trade execution data, is a significant plus.
• Ability to conduct market structure, market behavior and portfolio implementation research in both equity and fixed income markets.
• Build relationships with other teams supporting investment and research processes. Closely partner with multiple teams across the organization in the execution of joint research work.

You should possess the following qualifications:

• Excellent quantitative skills, as evidenced by formal training in statistics, applied mathematics, operations research, economics, computer science, physics, or related quantitative filed. Extensive experience in utilizing those skills in an applied research environment. A PhD is highly desirable.
• Minimum 1-3+ years of work experience in investment research function of a financial firm.
• A strong understanding of financial markets, including drivers of return, risk control and portfolio construction techniques.
• Strong understanding of the use of computer technology in financial and economic research, with statistical programming skills (Python, Java), data management and retrieval acumen (preferably SQL/Spark) and Linux literacy.
• Effective communication skills, both written and verbal.
• Strong understanding of data available in the investment management industry and experience in managing and accessing such data to support research efforts.
• Ability to work efficiently and multi-task effectively in a fast-paced and team-oriented environment. This will include end-to-end research project work under from data gathering to hypothesis testing and model implementation.

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 is anticipated to be between $160,000 and $300,000. The anticipated base pay range is based on information as of the time this post was generated. 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.