Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.

Tower is home to some of the worlds best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Responsibilities

• Being a subject matter expert, functionally and technically, to deliver security referential data needs for Towers global trading footprint
• Analyzing production issues and implementing corrective measures to prevent them from recurring
• Identifying various operational inefficiencies and developing automation efforts as part of the continuous improvement of the platform
• Interacting with trading teams and users to handle issues
• Strengthening and maintaining Towers security referential infrastructure to address trading and back-office needs
• Taking end-to-end ownership: development, testing, release, and support

Qualifications

The ideal candidate will have:

• A bachelors degree in computer science or a related field
• 2+ years of experience working in the financial trading industry
• Rich experience working with security referential data for financial trading across a variety of asset classes - equities, derivatives, FX, fixed income, crypto
• Brilliant problem-solving abilities
• The ability to manage multiple tasks in a fast-paced environment
• Proficiency in Python programming
• Strong expertise in SQL databases
• Familiarity working in an UNIX environment along with good shell scripting skills
• Excellent written and verbal English communication skills

Benefits

Towers headquarters are in the historic Equitable Building, right in the heart of NYCs Financial District and our impact is global, with over a dozen offices around the world.

At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.

Our benefits include:

• Generous paid time off policies
• Savings plans and other financial wellness tools available in each region
• Hybrid working opportunities
• Free breakfast, lunch and snacks daily
• In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
• Volunteer opportunities and charitable giving
• Social events, happy hours, treats and celebrations throughout the year
• Workshops and continuous learning opportunities

At Tower, youll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work together.

Tower Research Capital is an equal opportunity employer.