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 creative experts who are interested in applying machine learning to many types of problems, but particularly those with large amounts of noisy data.

When you work with us, you get to tackle tough problems alongside other scientists and engineers. People who will challenge your ideas. Who you can really learn from, and collaborate with. And you’re doing work that matters to a lot of people, too. Our investors include some of the world’s largest retirement funds, research institutions, educational endowments, healthcare systems and foundations. We admire what they do, and we’re proud to work with these organizations.

You will take on the following responsibilities:

Use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave
Apply machine learning to a vast array of datasets
Create and test complex investment ideas, use the latest machine learning tools, write code and partner with our engineers to test your hypotheses
Join our reading circles to stay up to date on the latest research papers in your field
Attend academic seminars to learn from thought leaders from top universities
Share insights from conferences focused on statistics, machine learning, and data science

You should possess the following qualifications:

Degree in a technical or quantitative discipline, like statistics, mathematics, physics, electrical engineering, or computer science (all levels welcome, from bachelor’s to doctorate)
Strong skills in at least one programming language (like C, C++, Java, or Python)
Understanding of the ins and outs of machine learning algorithms—and can tweak them as needed
Experience with applied machine learning to real-world datasets at scale
Published your work in journals and/or have presented at conferences

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 $300,000. 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.

Quantitative Researcher - Machine Learning