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Machine Learning Quant Jobs in Massachusetts (NOW HIRING)

Cisco

Principal Machine Learning Engineer

Boston, MA · On-site

$291K - $369K/yr

PhD in Computer Science, or related quantitative field, plus7+ years of industry research ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

Fidelity Investments

Quantitative Researcher

Boston, MA · On-site

$150K - $250K/yr

You will leverage standard and advanced tools from econometrics, statistics, stochastic calculus, machine learning, network graph analysis, etc. to pursue applications mostly for quant equities but ...

CarGurus

Senior Data Scientist

Boston, MA

Advanced degree (or proven experience) in Computer Science, Data Science, Mathematics, or any quantitative science which makes use of advanced data analytics or statistical or machine learning ...

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All JobsMachine Learning Quant JobsMachine Learning Quant Jobs in Massachusetts

Machine Learning Quant information

See Massachusetts salary details

$57.3K

$130.1K

$214.6K

How much do machine learning quant jobs pay per year?

As of Jun 9, 2026, the average yearly pay for machine learning quant in Massachusetts is $130,143.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,700.00 and $166,500.00 per year, depending on experience, location, and employer.

What is a Machine Learning Quant job?

A Machine Learning Quant is a specialist in quantitative finance who applies machine learning techniques to develop trading strategies, manage risk, and analyze financial data. They leverage statistical models, deep learning, and reinforcement learning to identify patterns in market data and optimize predictions. This role typically involves programming in Python or C++, working with large datasets, and collaborating with traders and researchers. Machine Learning Quants are employed by hedge funds, investment banks, and proprietary trading firms to gain a competitive edge in financial markets.

What are the key skills and qualifications needed to thrive in the Machine Learning Quant position, and why are they important?

To thrive as a Machine Learning Quant, you need strong skills in quantitative analysis, programming (often in Python or C++), statistical modeling, and a solid foundation in applied mathematics, typically supported by a degree in a quantitative field such as mathematics, physics, computer science, or engineering. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), financial data platforms, and certifications such as CFA or advanced degrees can be advantageous. Critical thinking, collaboration, and clear communication are key soft skills that enhance effectiveness in working with both technical and non-technical stakeholders. These competencies are crucial for building and validating models that inform high-stakes financial strategies and deliver value in fast-paced trading environments.

What are typical daily responsibilities for a Machine Learning Quant in a financial firm?

As a Machine Learning Quant, your day often involves researching and developing predictive models using large financial datasets, backtesting quantitative strategies, and optimizing algorithms for speed and accuracy. You'll collaborate closely with traders, data engineers, and other quants to implement models in live trading environments and refine them based on performance feedback. Regular activities also include monitoring new data sources, adjusting to changes in the market, and documenting your methodologies for regulatory or team review. This multidisciplinary work environment offers the opportunity to continuously learn and directly impact trading outcomes.

What are the most commonly searched types of Machine Learning Quant jobs in Massachusetts? The most popular types of Machine Learning Quant jobs in Massachusetts are:
What are popular job titles related to Machine Learning Quant jobs in Massachusetts? For Machine Learning Quant jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Machine Learning Quant jobs in Massachusetts look for? The top searched job categories for Machine Learning Quant jobs in Massachusetts are:
Machine Learning Quant jobs near you
Infographic showing various Machine Learning Quant job openings in Massachusetts as of June 2026, with employment types broken down into 41% Full Time, 33% Part Time, 7% Temporary, and 19% Contract. Highlights an 87% Physical, 6% Hybrid, and 7% Remote job distribution, with an average salary of $130,143 per year, or $62.6 per hour.
Manager, Algorithms and Machine Learning

Manager, Algorithms and Machine Learning

Beacon Biosignals

Boston, MA • On-site, Remote

$180K - $200K/yr

Full-time

PTO

Posted 29 days ago

Job description

Beacon Biosignals is on a mission to revolutionize precision medicine for the brain. We are the leading at-home EEG platform supporting clinical development of novel therapeutics for neurological, psychiatric, and sleep disorders. Our FDA 510(k)-cleared Waveband EEG headband and AI algorithms enable quantitative biomarker discovery and implementation. Beacon's Clinico-EEG database contains EEG data from nearly 100,000 patients, and our cloud-native analytics platform powers large-scale RWD/RWE retrospective and predictive studies. Beacon Biosignals is changing the way that patients are treated for any disorder that affects brain physiology.
Beacon Biosignals is seeking an Algorithms Manager to lead a group within the ML and Biomarker group. The ML and Biomarker group is responsible for building, productionizing, and maintaining the algorithmic systems that power Beacon's core capabilities, including machine learning model development, training and evaluation pipelines, biomarker development workflows, and the services that support reliable deployment and operation.
In this role, you will lead a team of 5-7 engineers and be accountable for the team's execution, health, and results. You will partner closely with technical and cross-functional stakeholders to translate company priorities into a clear roadmap, sound technical decisions, and strong team performance. This role reports to the Algorithms Senior Manager.
You are expected to bring sufficient technical depth in machine learning and algorithm development to evaluate approaches, guide tradeoffs, identify risks, and support high-quality decisions.
At Beacon, cultural and scientific impact comes from people who lead by example. We look for colleagues whose work reflects curiosity, sound judgment, a bias toward simplicity, a self-service mindset, and deep empathy for teammates, stakeholders, users, and patients. We believe diverse teams build more robust systems and achieve higher impact.
Beacon's asynchronous work practices support a strong remote experience, with in-person hubs in Boston, New York, and Paris. The Algorithms organization is distributed across American and European time zones. This role is located in the US, with a preference for candidates near our Boston or New York hubs.
What success looks like
As a successful manager at Beacon, you will:
  • Lead a high-performing Algorithms group through hiring, coaching, performance management, and clear expectations around ownership and impact.
  • Be accountable for the team's delivery against goals, ensuring alignment with Beacon's strategy, regulatory requirements, and quality standards.
  • Support engineer in making technical decisions across model development, biomarker pipelines, evaluation, and production systems, supporting the team in making sound tradeoffs.
  • Help your team scope out and prioritize tactical week-to-week work in direct connection with Beacon's wider strategic initiatives.
  • Ensure your team's development roadmap is outcome-oriented, up-to-date, aligned with the company's objectives and other teams' priorities, and communicated effectively to other stakeholders within Beacon.
  • Own project management responsibilities for team initiatives, including defining scope, managing timelines, and ensuring expectations are set both internally and externally.
  • Develop, refine, and own team-based processes that allow for efficient execution, communication, and coordination.
What you will bring
  • Experience managing a mid-sized ML or algorithm engineering team, with a track record of coaching, hiring, and growing individuals across levels while maintaining strong team health and accountability.
  • Proven ability to lead teams through technically complex, ambiguous work with cross-functional dependencies, balancing short-term delivery with longer-term capability building.
  • A strong depth of knowledge in algorithm/ML-model development, deploying production-ready ML systems, and model-maintenance to assess approaches, guide tradeoffs, and make sound decisions.
  • Experience operating within established frameworks and improving team-level ways of working, including prioritization, planning, and execution, while pragmatically addressing delivery friction and scaling challenges.
  • Strong communication and stakeholder management skills, with the ability to align partners around decisions, tradeoffs, and evolving plans, including in regulated or quality-sensitive environments.
  • A bias toward simplicity, with the ability to introduce the right level of process, avoid unnecessary complexity, and continuously improve how the team works.
  • Experience developing ML or algorithmic systems in regulated domains, with familiarity in regulatory submissions, including validation, reproducibility, documentation, and model governance requirements.

The salary range for this role is $180,000- $200,000. Salary ranges are determined using current market compensation data for this role and adjusted based on experience, skills, and location.The base salary is one component of the total compensation package, which includes equity, PTO and other benefits.
At Beacon, we've found that cultural and scientific impact is driven most by those that lead by example. As such, we're always seeking new contributors whose work demonstrates an avid curiosity, a bias towards simplicity, an eye for composability, a self-service mindset, and - most of all - a deep empathy towards colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.

Apply