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Algorithmic Execution Quant Jobs in Cambridge, MA

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Algorithmic Execution Quant information

See Cambridge, MA salary details

$57.4K

$130.2K

$214.8K

How much do algorithmic execution quant jobs pay per year?

As of Aug 24, 2026, the average yearly pay for algorithmic execution quant in Cambridge, MA is $130,245.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,800.00 and $166,700.00 per year, depending on experience, location, and employer.

What does an algorithmic execution quant do?

An Algorithmic Execution Quant is responsible for designing, developing, and optimizing algorithms that execute large financial trades efficiently and at minimal cost. They analyze market microstructure, create models to predict market impact, and work closely with traders and engineers to implement these strategies in real-time trading systems. Their work is essential in minimizing transaction costs and improving trade execution quality for their firm.

What are some common challenges faced by algorithmic execution quants when developing and deploying trading algorithms?

Algorithmic Execution Quants often encounter challenges such as adapting strategies to rapidly changing market conditions, managing latency and slippage, and ensuring compliance with regulatory requirements. They must also balance the need for innovation with the necessity for robust risk controls and system reliability. Collaboration with traders, developers, and risk managers is essential to refine algorithms and ensure they perform optimally in live trading environments.

What are the key skills and qualifications needed to thrive as an algorithmic execution quant, and why are they important?

To thrive as an Algorithmic Execution Quant, you need a strong background in quantitative analysis, programming (often in Python or C++), and a solid understanding of financial markets, typically supported by an advanced degree in a quantitative discipline. Proficiency with statistical modeling tools, trading platforms, and market data systems, as well as familiarity with technologies like FIX protocol, is crucial. Strong problem-solving ability, attention to detail, and effective communication help you collaborate across trading, research, and technology teams. These skills are essential for designing, optimizing, and maintaining robust trading algorithms that achieve best execution and mitigate risk in fast-moving markets.

What is the difference between Algorithmic Execution Quant vs Quantitative Trader?

AspectAlgorithmic Execution QuantQuantitative Trader
Primary FocusDeveloping and implementing algorithms for trade execution to minimize market impactCreating trading strategies to generate alpha and profit from market movements
Work EnvironmentQuantitative research teams, trading desks, technology-drivenTrading floors, portfolio management teams, research departments
Required SkillsProgramming, market microstructure, execution algorithmsQuantitative modeling, market analysis, strategy development

While both roles involve quantitative skills, an Algorithmic Execution Quant specializes in optimizing trade execution processes, whereas a Quantitative Trader focuses on developing strategies to generate profits. The roles often collaborate but serve different functions within trading firms.

What are popular job titles related to Algorithmic Execution Quant jobs in Cambridge, MA?

For Algorithmic Execution Quant jobs in Cambridge, MA, the most frequently searched job titles are:

What job categories do people searching Algorithmic Execution Quant jobs in Cambridge, MA look for?

The top searched job categories for Algorithmic Execution Quant jobs in Cambridge, MA are:

What cities near Cambridge, MA are hiring for Algorithmic Execution Quant jobs?

Cities near Cambridge, MA with the most Algorithmic Execution Quant job openings:

Algorithmic Execution Quant jobs near you
Infographic showing various Algorithmic Execution Quant job openings in Cambridge, MA as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $130,245 per year, or $62.6 per hour.

Data Scientist, Trading Operations

Boston, MA • On-site

Quant Blueprint LLC
See more jobs at Quant Blueprint LLCexternal

$85 - $120/hr

Other

Posted 19 days ago

Job description

Voleon is a technology company that applies state‑of‑the‑art machine‑learning techniques to real‑world problems in finance. For over a decade, we have led our industry and worked at the frontier of applying machine‑learning to investment management. We have become a multibillion‑dollar asset manager, and we have ambitious goals for the future.

Your colleagues will include internationally recognized experts in machine‑learning research as well as highly experienced technology and finance professionals. The people who shape our company come from other backgrounds, including concert music performances, humanitarian aid, opera singing, sports writing, and BMX racing. You will be part of a team that loves to succeed together.

In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.

The Voleon Group has formed a new team to help advance our data‑driven investment initiatives. As a Data Scientist, you will be responsible for harvesting insights from a complex array of data. Your role will involve data curation, analysis, interpretation, visualization, and communication of your findings to members of the research staff and executive leadership. This role is a means to make a difference: as a machine‑learning company, data insights are essential to our business.

As a Data Scientist in Trading Operations, you will be embedded in the Quantitative Trading Strategy team. The team focuses on domain‑heavy technical work, such as tuning execution algorithms and optimizing portfolio financing. You will build, maintain, and analyze data pipelines to generate insight consumed by the whole team. You will work at the intersection of trading and research on problems requiring market domain expertise and statistical and quantitative rigor.

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