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Scientific Machine Learning Jobs in Massachusetts

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

Proficiency in Python and familiarity with the Python data science stack (NumPy, SciPy, Pandas ... Familiarity with machine learning and statistical modeling fundamentals, including model evaluation ...

Varsity Tutors

Machine Learning Tutor

Cambridge, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Newton, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Harvard University

Machine Learning Engineer

Boston, MA · On-site

$60/hr

... Machine Learning Engineer with advanced expertise to lead development of large language models ... CCB provides computational and analytic resources to advance scientific discovery within HMS ...

Harvard University

Machine Learning Engineer

Boston, MA · On-site +1

... Machine Learning Engineer with advanced expertise to lead development of large language models ... CCB provides computational and analytic resources to advance scientific discovery within HMS ...

Varsity Tutors

Machine Learning Tutor

Lawrence, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Lowell, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Waltham, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Northampton, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Boston, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Quincy, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Lynn, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Somerville, MA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Axon

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Massachusetts

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Massachusetts? For Scientific Machine Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Massachusetts look for? The top searched job categories for Scientific Machine Learning jobs in Massachusetts are:
What cities in Massachusetts are hiring for Scientific Machine Learning jobs? Cities in Massachusetts with the most Scientific Machine Learning job openings:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Machine Learning Analyst

Bracebridge Capital

Boston, MA • On-site

$110K - $145K/yr

Full-time

Posted 23 days ago

Job description

Bracebridge Capital, LLC is a leading alternative asset manager with approximately $12 billion of net assets under management. The firm pursues investment strategies primarily within the global fixed income markets with the objectives of capital preservation and absolute return without significant correlation to equity, interest rate and foreign exchange markets. Established in 1994, Bracebridge manages private investment funds that serve endowments, foundations, pension funds and other institutional and high-net-worth investors.
Approximately 170 employees operate from our office located in Boston's historic Back Bay. The entrepreneurial and collaborative culture at Bracebridge rewards and supports motivated, dedicated, enthusiastic and intellectually curious individuals. We believe our firm's greatest asset is the people who work here.
We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning team. The team's primary mission is to develop machine learning systems to answer open-ended investment questions and support portfolio management decisions. The team works across the project lifecycle and technical stack, from ideation, understanding and analyzing data, hypothesis generation and testing, and model development all the way through to the deployment and maintenance of models and systems in production. Our work spans statistical modeling, classical machine learning, and modern AI and LLM techniques.
The Machine Learning Analyst's primary responsibility will be to contribute to these efforts alongside other team members. Over time, you will develop the technical and domain expertise needed to take increasing ownership of individual components and ultimately end-to-end projects.
The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to translate loosely defined investment ideas into practical tools and models. Successful candidates will have solid programming foundations, be comfortable translating between qualitative and quantitative descriptions of problems and be excited to build data analysis and machine learning systems against the backdrop of portfolio management.
Since the team works closely with trading floor personnel to assist with portfolio management decision-making, an interest in economic and financial markets is essential, but no specific prior experience is necessary.
This role is open to candidates available to begin in the near term, as well as students expecting to complete their undergraduate degree between Fall 2026 and Summer 2027. Start dates will be determined based on candidate availability and, for students, degree completion.
Responsibilities:
  • Collaborate closely with Machine Learning team members, portfolio managers, and researchers to translate open-ended investment questions into well-defined analytical and machine learning problems
  • Develop and evaluate data-driven machine learning and quantitative models, including simulation- and optimization-based approaches, for investment-related problems
  • Contribute to maintaining existing models and analytic tools in production
  • Over time, take ownership of individual features and components and full projects
  • Clearly document and communicate methods, assumptions, results, and limitations of models to other researchers and trading professionals across the firm
  • Stay current with relevant new techniques and technologies in machine learning and artificial intelligence, particularly as they pertain to finance and investing

Qualifications:
  • Bachelor's degree (or equivalent) in a rigorous quantitative field
  • 0-2 years of experience through industry internships, undergraduate research or thesis, or substantial independent technical projects involving software development, data analysis, or machine learning
  • Proficiency in Python and familiarity with the Python data science stack (NumPy, SciPy, Pandas, scikit-learn, etc), with experience in other languages a plus
  • Experience working with and analyzing data from multiple sources and in multiple formats
  • Familiarity with machine learning and statistical modeling fundamentals, including model evaluation and experimental design
  • Demonstrated ability to independently scope and execute open-ended technical projects
  • Interest in financial markets, intellectual curiosity, and comfort in working on open-ended problems
  • Strong written and verbal communication skills

Current anticipated annual base salary range: $110,000 - $145,000
Base salary within the range will be determined by various factors including but not limited to the individual's experience, skills and qualifications.

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