Quantitative Researcher: Machine Learning
New York, New York, United States
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- 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 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
- Degree in a technical or quantitative discipline, like statistics, mathematics, physics, electrical engineering, or computer science (all levels welcome, from bachelor’s to doctorate)
- Intermediate 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
- Published your work in journals and/or have presented at conferences
- 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.