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Algorithmic Trading Jobs in Boston, MA (NOW HIRING)

Draper

Senior Navigation Algorithm Engineer

Cambridge, MA · On-site

$75K - $245K/yr

... trades to support a design. • Designs algorithms using modern theory and proven techniques. • Develops embedded software based on prototype algorithms. • Analyzes designs to demonstrate ...

Draper

Senior Navigation Algorithm Engineer

Cambridge, MA · On-site +1

$75K - $245K/yr

... trades to support a design. Designs algorithms using modern theory and proven techniques. Develops embedded software based on prototype algorithms. Analyzes designs to demonstrate performance and ...

Bose Corporation, U.S.A

Senior Systems Engineer

Framingham, MA · On-site

$107K - $147K/yr

... algorithms, embedded systems, acoustics, cloud-connected experiences, and mobile applications. * Use model-based and analytical approaches to evaluate alternatives, guide trade-off decisions, and ...

Bose Corporation

Senior Systems Engineer

Framingham, MA · On-site

$107K - $147K/yr

... algorithms, embedded systems, acoustics, cloud-connected experiences, and mobile applications. * Use model-based and analytical approaches to evaluate alternatives, guide trade-off decisions, and ...

Boseallaboutme

Senior Systems Engineer

Framingham, MA · On-site

$107K - $147K/yr

... algorithms, embedded systems, acoustics, cloud-connected experiences, and mobile applications. * Use model-based and analytical approaches to evaluate alternatives, guide trade-off decisions, and ...

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All JobsAlgorithmic Trading JobsAlgorithmic Trading Jobs in Boston, MA

Algorithmic Trading information

See Boston, MA salary details

$80.9K

$93.2K

$102.1K

How much do algorithmic trading jobs pay per year?

As of Sep 14, 2026, the average yearly pay for algorithmic trading in Boston, MA is $93,157.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,000.00 and $98,900.00 per year, depending on experience, location, and employer.

What is algorithmic trading?

Algorithmic trading involves trading in equities, currencies, or other financial instruments using computer programs. A trading program uses an algorithm to calculate current market conditions. This trading method is automated, so the program buys or sells the financial instrument when the algorithm says that the market meets all the requirements for a profitable trade. To create an algorithm, you perform mathematical and statistical analysis, also known as quantitative analysis, on an exchange or equity. After creating an algorithm with defined trading rules, you test it using historical market data. While this is primarily a technical field, you also need an understanding of the market.

What is algorithmic trading?

Algorithmic trading refers to the use of computer programs and algorithms to automatically execute trading orders in financial markets. These algorithms follow predefined rules based on factors like price, timing, and volume to optimize trading strategies and reduce human intervention. Algorithmic trading is widely used by institutional investors, hedge funds, and individual traders to increase efficiency, minimize costs, and capitalize on market opportunities. It can range from simple rule-based systems to complex strategies involving machine learning and artificial intelligence.

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

To thrive as an Algorithmic Trader, you need a strong background in quantitative analysis, programming (often Python, C++, or Java), and a solid understanding of financial markets, typically supported by a degree in mathematics, engineering, finance, or computer science. Familiarity with statistical modeling tools, trading platforms, and backtesting systems is essential, and certifications such as CFA or FRM can be advantageous. Superior problem-solving skills, attention to detail, and the ability to work under pressure set standout professionals apart in this field. These skills are crucial to developing, implementing, and refining trading strategies that can operate profitably and reliably in fast-moving financial environments.

What are the main challenges faced by professionals in algorithmic trading, and how can they be addressed?

Professionals in algorithmic trading often encounter challenges such as developing strategies that remain effective in rapidly changing markets, minimizing latency for faster execution, and managing the risks associated with automated trading systems. To address these challenges, it's essential to stay updated with the latest market trends and technological advancements, conduct rigorous backtesting of algorithms, and implement robust risk management protocols. Collaboration with quantitative analysts, software engineers, and risk managers is also key to ensuring strategies are both innovative and resilient.

What is the difference between Algorithmic Trading vs Quantitative Analyst?

AspectAlgorithmic TradingQuantitative Analyst
Required CredentialsDegree in finance, computer science, or related field; programming skillsDegree in mathematics, statistics, or finance; strong analytical skills
Work EnvironmentTrading firms, hedge funds, financial institutions; fast-pacedInvestment banks, asset management firms; research-focused
Employer & Industry UsageUsed to automate trading strategiesDevelops models to inform trading decisions

While both roles involve quantitative skills and finance knowledge, Algorithmic Traders focus on implementing automated trading systems, whereas Quantitative Analysts develop models and strategies that may be used by traders or firms. The roles often overlap but differ mainly in their primary focus: execution versus modeling.

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Algorithmic Trading jobs near you
Infographic showing various Algorithmic Trading job openings in Boston, MA as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 8% Part Time, 1% Temporary, and 3% Contract. Highlights an 79% Physical, 7% Hybrid, and 14% Remote job distribution, with an average salary of $93,157 per year, or $44.8 per hour.

Data Scientist, Trading Operations

Boston, MA • On-site

Quant Blueprint LLC
See more jobs at Quant Blueprint LLCexternal

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This job post has expired today. Applications are no longer accepted.

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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