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Part Time Data Scientist Jobs in Boston, MA (NOW HIRING)

NorthEastern

Part-Time Lecturer MGEN (Boston)

Boston, MA · On-site

$2.6K/wk

... so that data scientists and business analysts can access and interpret data in context to provide meaningful results to management. The MS in Software Engineering Systems approaches software ...

IQVIA

MedTech

Boston, MA · On-site

$39 - $42/hr

We believe in pushing the boundaries of human science and data science to make the biggest impact ... part-time). Dependent on the position offered, incentive plans, bonuses, and/or other forms of ...

NorthEastern

Part-Time Lecturer - Analytics

Boston, MA · On-site

$1.5K/wk

This degree prepares students for entry- and mid-level roles in analytics, such as data analyst ... Preference for candidates with a PhD in a sciences field, or similar. Demonstration of teaching ...

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All JobsData Scientist JobsPart Time Data Scientist JobsPart Time Data Scientist Jobs in Boston, MA

Part Time Data Scientist information

See Boston, MA salary details

$40.7K

$133.3K

$213.5K

How much do part time data scientist jobs pay per year?

As of Sep 4, 2026, the average yearly pay for part time data scientist in Boston, MA is $133,336.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $147,700.00 per year, depending on experience, location, and employer.

What is a part time data scientist?

A part time data scientist is a professional who applies statistical analysis, machine learning, and data processing skills to extract insights from data, but works fewer hours than a full-time employee—typically under 35 hours per week. Part time data scientists may work for one or more companies, often on flexible schedules or as contractors. Their responsibilities can include data cleaning, building predictive models, and presenting data-driven insights to help organizations make informed decisions. This role is ideal for those seeking work-life balance, students, or professionals looking to supplement their income.

What does a part-time data scientist do?

A part-time data scientist’s skills and responsibilities are very similar to those of a data analyst. Like a data analyst, you have to collect and review company or industry data and then perform an analysis based on a business question the company wants to answer. You share this information with other parts of the enterprise. Where data scientists’ duties are different is that you use past data to build machine learning models. These machine learning models make predictions, and the goal is to identify trends that lead to a more thorough understanding of the business and its customers.

What are the key skills and qualifications needed to thrive as a part-time data scientist, and why are they important?

To thrive as a Part Time Data Scientist, you need strong analytical skills, proficiency in statistics, and experience with data modeling, typically supported by a degree in a quantitative field. Familiarity with tools like Python, R, SQL, and data visualization platforms, as well as knowledge of machine learning libraries, is often required. Excellent problem-solving, time management, and communication skills help you effectively deliver insights and collaborate despite reduced hours. These skills ensure you can provide high-impact, actionable analyses efficiently within a limited work schedule.

How does working part-time as a data scientist typically impact project involvement and collaboration with full-time team members?

As a part-time data scientist, you may be assigned to specific projects or tasks that fit within your available hours, often focusing on defined deliverables or analytical support roles. Collaboration with full-time colleagues is common, usually through regular meetings, shared documentation, and communication tools to ensure alignment. It's important to clearly communicate your schedule and capacity, as timely updates and hand-offs help maintain project momentum. While you might not be involved in every stage of a project, your specialized contributions are highly valued, and many organizations foster flexible, inclusive environments to integrate part-time professionals effectively.

What is the difference between Part Time Data Scientist vs Data Analyst?

AspectPart Time Data ScientistData Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's degree in Data Analysis, Statistics, or related field
Work EnvironmentFlexible hours, project-based, often remoteOffice or remote, regular hours, structured projects
Employer & Industry UsageTech companies, startups, consulting firmsBusiness, finance, marketing, healthcare
Common Search & ComparisonPart Time Data Scientist vs Data Analyst

Part Time Data Scientists focus on advanced analytics, machine learning, and modeling, often requiring higher technical skills and specialized knowledge. Data Analysts typically handle data cleaning, reporting, and visualization. While both roles analyze data, Part Time Data Scientists work on complex models and predictive analytics, whereas Data Analysts focus on descriptive insights. The choice depends on your skills and career goals within data roles.

More about Part Time Data Scientist jobs

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

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

What are popular job titles related to Part Time Data Scientist jobs in Boston, MA?

For Part Time Data Scientist jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Part Time Data Scientist jobs in Boston, MA look for?

The top searched job categories for Part Time Data Scientist jobs in Boston, MA are:

What cities near Boston, MA are hiring for Part Time Data Scientist jobs?

Cities near Boston, MA with the most Part Time Data Scientist job openings:

Part Time Data Scientist jobs near you
Infographic showing various Part Time Data Scientist job openings in Boston, MA as of August 2026, with employment types broken down into 3% Full Time, and 97% Part Time. Highlights an 97% In-person, and 3% Remote job distribution, with an average salary of $133,336 per year, or $64.1 per hour.

Evidence, Provenance and Analytical-Workflow Specialists - Remote

Axyde Analytics

Boston, MA • On-site, Remote

$150 - $300/hr

Part-time

Posted 11 days ago

Job description

Work arrangement: Remote within the United States, with potential international travel
Engagement: Contingent, part-time/on-call specialist
Anticipated compensation: $150-$300 per hour, depending on qualifications and assignment, or a negotiated fixed price by work package. $300 per hour is the maximum anticipated rate.
Opportunity
Axyde Analytics is assembling a multidisciplinary expert team for anticipated U.S. government-funded project-scoping assignments involving critical minerals and international infrastructure.
We seek specialists capable of designing and operating evidence-traceability, provenance, analytical-workflow, data-integration and decision-support systems for complex technical and commercial assessments.
Potential assignments may require integrating geological, engineering, environmental, market, financial, sponsor, regulatory and field evidence into transparent, reproducible findings and recommendations.
Axyde does not expect one candidate to cover every data and analytical discipline. Applicants should identify the evidence, provenance, workflow and data-governance areas in which they possess direct, demonstrable expertise.
Specialist Tracks
We are recruiting experts in one or more of the following tracks:
  • Evidence registers and source lineage
  • Data provenance and chain of custody
  • Multi-source data integration
  • Structured analytical techniques
  • Decision analysis and assumption management
  • Data-quality assessment and discrepancy resolution
  • Technical-document and workpaper control
  • Requirements and obligation traceability
  • Model-input, formula and output governance
  • Geospatial and tabular data integration
  • Mineral supply-chain provenance and traceability
  • Auditability, reproducibility and records management
  • Analytical workflow and configuration management
  • Role-based access and information protection
  • Data visualization and decision dashboards
  • Automated quality-control and exception detection
  • Cybersecurity and data-governance interfaces
  • Independent analytical and evidence review

Potential Responsibilities
Depending on the assignment and specialist track, selected experts may:
  • Establish controlled evidence, source, assumption, decision and action registers.
  • Record source, date, owner, confidence, limitation and decision effect for material evidence.
  • Integrate technical, commercial, financial, environmental, regulatory and field information.
  • Reconcile conflicting data, units, currencies, dates, definitions and assumptions.
  • Distinguish primary evidence, sponsor-supplied information, independent sources and analytical judgment.
  • Establish traceability from assignment requirements through analysis, findings and recommendations.
  • Develop reproducible workflows for calculations, models, technical reviews and deliverables.
  • Control versions, changes, comments, approvals and release records.
  • Evaluate data completeness, reliability, representativeness and fitness for the decision.
  • Design dashboards showing evidence gaps, assumptions, risks, decisions and acceptance status.
  • Support mineral provenance, chain-of-custody and responsible-sourcing assessments.
  • Review cybersecurity, access, storage, retention and information-sharing requirements.
  • Develop automated checks for missing evidence, inconsistent assumptions and unresolved exceptions.
  • Support vertical review from conclusion through calculation to source evidence.
  • Support horizontal review across technical, economic, schedule, budget and recommendation sections.
  • Identify decisive information gaps and assign validation tasks, owners and decision dates.
  • Prepare sanitized, Government-visible staffing or analytical decision records when directed.
  • Support international teams working across disciplines, organizations, languages and time zones.
  • Prepare concise workflow, evidence-quality and decision-support findings.
  • Serve as a workflow lead, data lead, contributor, alternate or independent analytical reviewer.

Required Qualifications
Candidates should possess:
  • At least 7-10 years of directly relevant analytical, data-governance, evidence-management, audit, intelligence, engineering, scientific or technical-delivery experience.
  • A degree in data science, information systems, engineering, physical science, geospatial science, intelligence studies, statistics, operations research, library/information science or a closely related field.
  • Direct responsibility for identifiable evidence-intensive technical, scientific, engineering, financial, intelligence or government decision-support efforts.
  • Demonstrated ability to make complex analytical work traceable, reproducible, reviewable and decision-oriented.
  • Experience integrating structured and unstructured information from multiple sources.
  • Experience designing or independently reviewing controlled analytical workflows, models, repositories or decision records.
  • Strong written and verbal English-language communication skills.
  • Ability to collaborate with technical experts without substituting workflow mechanics for professional judgment.
  • Either U.S. citizenship or lawful permanent-resident status in the United States.
  • Legal authorization to work in the United States without current or future sponsorship.
  • Willingness and ability to travel internationally when an assignment requires it.
  • No known employment, confidentiality, intellectual-property, noncompete, data-access or conflict-of-interest restriction that would prevent participation.

Experience involving mining, critical minerals, infrastructure, geospatial analysis, government acquisition, international development, audit, quality assurance or regulated technical environments is particularly valuable.
Application Information Requested
Please submit a résumé and a brief response identifying:
  1. Your strongest evidence, provenance, data-integration or analytical-workflow specialties.
  2. The technical, scientific, engineering, intelligence, financial or government environments in which you have applied them.
  3. Up to five representative systems, projects or analytical efforts and your personal responsibilities on each.
  4. Your experience with evidence lineage, assumption control, discrepancy resolution, reproducibility or independent review.
  5. The workflow, data, geospatial, visualization or governance tools you are qualified to use or review.
  6. Your experience protecting confidential, proprietary, business-sensitive or Government information.
  7. Countries and regions in which you have worked.
  8. Whether you can serve as a workflow lead, independent reviewer, or both.
  9. Your current U.S. location.
  10. Whether you are a U.S. citizen or lawful permanent resident.
  11. Your availability during the next 30 days.
  12. Your ability to travel internationally and any geographic restrictions.
  13. Your anticipated hourly rate.
  14. Any actual or potential conflicts involving governments, project sponsors, technology providers, consulting firms or current employers.

Engagement Conditions
This is a contingent opportunity supporting anticipated government-funded assignments. No employment, contract award, minimum workload or particular assignment is guaranteed.
Selection for an assignment will depend on contract award, analytical and data requirements, qualifications, availability, eligibility, conflicts, travel requirements, mutually acceptable compensation and execution of appropriate employment or consulting documentation.
Axyde may tailor and reformat selected résumés for proposal compliance without materially changing the candidate's qualifications or experience.
Axyde Analytics
Strategic minerals •Supply-chain security •U.S. industrial base

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