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Volunteer Data Scientist Machine Learning Jobs in Boston, MA

Implement, train, and evaluate machine learning models using Python and AWS SageMaker. * Develop ... Design A/B tests of the Data Science team's models and analyze their results * Communicate ...

Sr. Data Scientist

Framingham, MA · On-site

$120K - $165K/yr

  • Medical

  • Retirement

Data science, machine learning, and analytics are a crucial part of this mission. These capabilities fuel the creation of new and innovative products, helping us to bring the right products to the ...

Sr. Data Scientist

Framingham, MA · On-site

$120K - $165K/yr

  • Medical

  • Retirement

Data science, machine learning, and analytics are a crucial part of this mission. These capabilities fuel the creation of new and innovative products, helping us to bring the right products to the ...

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Volunteer Data Scientist Machine Learning information

See Boston, MA salary details

$40.7K

$133.3K

$213.5K

How much do volunteer data scientist machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for volunteer data scientist machine learning in Boston, MA is $133,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $147,800.00 per year, depending on experience, location, and employer.

What does a volunteer data scientist machine learning do?

A Volunteer Data Scientist in Machine Learning applies data analysis and machine learning techniques to help organizations solve problems, often for nonprofits or community projects. They may work on tasks such as cleaning and analyzing datasets, building predictive models, or creating data visualizations. Their work supports impactful decision-making and can help organizations operate more efficiently or achieve specific social goals. Volunteers often collaborate with teams to define project objectives and deliver actionable insights using their technical expertise.

What skills and qualifications are needed to thrive as a volunteer data scientist machine learning?

To thrive as a Volunteer Data Scientist (Machine Learning), you need proficiency in statistics, data analysis, programming (Python or R), and a foundational understanding of machine learning algorithms, often supported by a relevant degree or online certifications. Familiarity with tools like scikit-learn, TensorFlow, Jupyter Notebooks, and data visualization platforms is typically required. Strong problem-solving abilities, teamwork, and effective communication are crucial soft skills for translating complex data insights to non-technical stakeholders. These skills and qualities are essential to effectively contribute value, support decision-making, and drive impact in resource-limited volunteer environments.

How does a volunteer data scientist machine learning typically collaborate with other team members or departments?

As a Volunteer Data Scientist specializing in Machine Learning, you will often work closely with cross-functional teams such as project managers, software engineers, and subject matter experts. Effective collaboration is essential, as you may need to clarify project goals, source and preprocess data, or translate complex findings for non-technical stakeholders. Regular meetings and open communication help ensure that your machine learning solutions are aligned with the organization's mission and that your insights are actionable. This collaborative environment provides valuable experience working in diverse teams and often leads to impactful, real-world applications of your technical skills.

What is the difference between Volunteer Data Scientist Machine Learning vs Volunteer Data Analyst?

AspectVolunteer Data Scientist Machine LearningVolunteer Data Analyst
Required CredentialsKnowledge of machine learning algorithms, programming skills (Python, R), basic statisticsProficiency in data visualization, basic statistics, Excel, SQL
Work EnvironmentCollaborative projects, research-focused, often remote or nonprofit settingsData reporting, dashboard creation, data cleaning in nonprofit or community projects
Employer & Industry UsageTech nonprofits, research institutions, startupsCharities, educational organizations, community initiatives

Volunteer Data Scientist Machine Learning focuses on developing predictive models and advanced analytics, requiring programming and machine learning expertise. Volunteer Data Analyst emphasizes data interpretation, visualization, and reporting. Both roles support nonprofits but differ in technical complexity and focus areas.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Boston, MA?

The most popular types of Data Scientist Machine Learning jobs in Boston, MA are:

Senior or Principal Data Scientist/Machine Learning Scientist

Datalign Advisory, Inc.

Cambridge, MA • On-site

Full-time

Medical, Dental, Vision, Retirement

Re-posted 9 days ago


Job description

Position Overview
We are seeking a Senior or Principal Data Scientist/Machine Learning Scientist to lead product-focused artificial intelligence initiatives and facilitate strategic decision-making through advanced analytics and machine learning. This role requires a proven track record of building and scaling data science products that directly impact user experience and business outcomes.
As Data Scientist/Machine Learning Scientist, you will shape the future of how consumers connect with vetted financial advisory firms through our proprietary three-sided marketplace, leveraging data and AI-powered analytics to create meaningful one-to-one matches and improved financial outcomes.
Please note: We are only accepting applications from candidates in the Greater Boston area, as this is a hybrid role with 4 days a week in office.
Key Responsibilities
  • Conduct exploratory data analysis to uncover relationships, patterns and key features in data for both business decision making and model development.
  • Develop and deploy machine learning models for production using robust CI/CD practices in collaboration with software engineers.
  • Identify success metrics and build evaluation frameworks for both model and product performance considering both technical and business requirements.
  • Innovate with the latest generative AI and graph-based machine learning advancements to improve existing processes and develop new products.
  • Contribute to architectural and code reviews to maintain and evolve the health of our technical stack.
  • Collaborate with product management, engineering, and business teams to rapidly identify and test high-impact solutions for business needs.
  • Influence strategic decisions across multiple business areas by clearly communicating complex data in a way that is understandable and actionable for technical and non-technical stakeholders.

Required Qualifications
  • MS or PhD in Computer Science, Statistics, Mathematics, or related quantitative field
  • MS with 6+ years of industry experience or PhD with 3+
  • Entrepreneurial mindset with willingness to experiment, iterate quickly and move from hypothesis to implementation to develop critical business solutions.
  • Expert-level proficiency in Python, SQL, and distributed computing frameworks.
  • Deep understanding of machine learning algorithms, experiment design and statistical modeling and evaluation
  • Strong background in product analytics, classifiers, recommendation systems, and personalization algorithms
  • Experience putting machine learning solutions in production with modern ML platforms (e.g. AWS/GCP/Azure ML, MLflow, Kubeflow)
  • Familiarity with A/B testing, product metrics and user behavior analytics

Preferred Qualifications
  • Experience with graph representations/graph neural networks, real-time ML systems and/or matching algorithms.
  • Proficiency in big data technologies (e.g. Spark, Dask, Kafka, Airflow) and cloud architectures.
  • Background in fintech, wealth management, or financial advisory services with an understanding of the regulatory requirements in financial services.
  • Track record of publications in top-tier conferences or journals.
  • Understanding of marketplace dynamics and multi-sided platform optimization.
  • Experience with data monetization and building data products

What We Offer
  • A dynamic, team-centric and supportive environment in the heart of Kendall Square where your work has a direct impact on enhancing financial advisory services.
  • Competitive salary with performance-based bonuses.
  • Comprehensive benefits package including health, dental, and vision insurance, and retirement savings plan
  • Commuting is on us and we will pay for your monthly parking, T Pass or commuter rail pass. We also offer a corporate Bluebike membership.
  • Opportunities for professional growth and development within a rapidly growing company.
  • Weekly lunches catered to the office.
  • Fully stocked kitchen covering all of coffee, tea and snack needs.

Additional Information
  • We are only accepting applications from candidates in the Greater Boston area, as this is a hybrid role with 4 days a week in office.
  • The level of this position can be adjusted based on the candidate's experience.