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Part Time Data Science Jobs in Waltham, MA (NOW HIRING)

Wit

Adjunct Instructor - Interior Design

Boston, MA · On-site

$1.3K/wk

In addition, we are seeking a part-time adjunct faculty member to lead History of Interiors I (MW ... Architecture and Design, Computing and Data Science, Engineering, Management, and Sciences and ...

Wit

Adjunct Instructor

Boston, MA

$1.3K/wk

... as part-time adjunct faculty for the Civil Engineering Program to teach Senior Capstone ... Data Science, Engineering, Management, and Sciences and Humanities. Wentworth is a member of the ...

C10 Labs

AI BioHub Mentor

Cambridge, MA · On-site +1

... in assessing scientific feasibility, technical differentiation, data strategy, validation ... Engagement This is a part-time mentor appointment. Time commitments will vary based on program ...

Stantec

Environmental/Wetland Scientist

Burlington, MA · On-site

$67K - $97K/yr

... data collection technologies is desired. * Knowledge of computer applications and functions ... Regular full-time and part-time employees (working at least 20 hours per week) have access to ...

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All JobsData Science JobsPart Time Data Science JobsPart Time Data Science Jobs in Waltham, MA

Part Time Data Science information

What are part-time data science jobs?

Part-time data science jobs focus on the collection, analysis, and manipulation of data sets. In this role, you can either work for one employer or freelance on a per-project basis. As a data scientist or data analyst, you mine and analyze information. Your duties also include using statistics and math on the data sets to develop algorithms and models that perform specific processes or aid with your employer’s decision-making. Machine learning engineers use data to create algorithms that help computers and machines process information in structured and unstructured environments and make decisions or take actions based on the data.

What is a part-time data science job?

A part-time data science job involves working fewer hours than a full-time data scientist, typically less than 40 hours per week. Part-time data scientists perform many of the same tasks as their full-time counterparts, such as analyzing data, building models, and generating insights to help organizations make data-driven decisions. These roles are ideal for students, professionals seeking additional income, or those looking for flexible work arrangements. Part-time positions may be project-based or ongoing, and can be found in various industries including tech, healthcare, finance, and retail.

How do part-time data science roles typically structure team collaboration and project ownership?

In part-time data science positions, collaboration is often facilitated through regular virtual meetings, shared project management tools, and clear documentation. Part-time data scientists usually work on specific projects or components, such as data cleaning, exploratory analysis, or building models, while maintaining close communication with full-time team members and stakeholders. This structure allows for flexibility but also requires strong self-management and proactive updates to ensure alignment with the broader team's objectives. Many organizations use agile methodologies to assign tasks and track progress, making it easier for part-time contributors to integrate their work seamlessly.

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, statistical knowledge, and proficiency in programming languages like Python or R, often supported by a degree in a quantitative field. Familiarity with data analysis tools, machine learning libraries, and platforms such as SQL, Jupyter, or Tableau is typically required. Effective communication, time management, and problem-solving abilities help you deliver impactful insights within limited hours. These skills ensure you can efficiently analyze data, present findings clearly, and drive value for organizations even with part-time commitment.
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Part Time Data Science jobs near you
Infographic showing various Part Time Data Science job openings in Waltham, MA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Temporary Micro-Credential Grader - JSD- Microcredential Grader-AI Fundamentals for STEM Professiona

Brandeis University

Waltham, MA • On-site

$25 - $30/hr

Part-time

Re-posted 17 days ago

Job description

Position: Micro-Credential Grader-AI Fundamentals for STEM Professionals
Location: Fully remote (U.S.-based applicants only, no visa sponsorships)
Division: Rabb School of Continuing Studies, Brandeis University
Type: Part-Time, 4 months, varying hours, no more than 25 hours per week
Compensation: Hourly $25-$30
Reports to: Assistant Dean of Education and Learning Innovation
Brandeis University's Rabb School of Continuing Studies is seeking a detail-oriented STEM professional to serve as a Micro-Credential Grader for the online asynchronous credential, AI Fundamentals for STEM Professionals.
In this fully remote, short-term hourly position, you'll evaluate learner submissions that demonstrate mastery of AI concepts through a real-world STEM challenge and a complete 5-step workflow design. This project-based credential equips professionals with foundational skills in supervised learning, data preprocessing, model selection, and ethical AI deployment. As a grader, you'll apply structured rubrics to assess technical accuracy, conceptual depth, and responsible innovation.
This role offers a unique opportunity to contribute to a high-impact, workforce-aligned credential that bridges STEM expertise with emerging AI capabilities.
What You Will Do:
  • Evaluate learner submissions of the AI Workflow Project, which include a real-world STEM challenge, an AI-powered solution, and a complete 5-step workflow design.
  • Apply structured rubrics to assess mastery of skills such as supervised learning, data preprocessing, model selection, and interpretability.
  • Participate in calibration exercises with fellow graders (if needed) to ensure consistency in evaluating technical artifacts and conceptual reasoning.
  • Maintain confidentiality and objectivity throughout the grading process

What You Bring:
  • Bachelor's degree required; Master's degree preferred in Computer Science, Data Science, Engineering, or related STEM disciplines.
  • Subject-matter expertise in foundational AI concepts, including machine learning, data analysis, and ethical considerations in AI deployment.
  • Experience in academic assessment, workforce development, or digital learning preferred.
  • Familiarity with learning management systems (Moodle preferred), online credentialing platforms, and collaborative grading workflows.
  • Professional, learner-centered approach with a commitment to academic integrity and continuous improvement. Proficient in rubric-based assessment and competency validation, especially for technical and project-based submissions.
  • Strong attention to detail and ability to maintain consistency across diverse submissions.
  • Excellent written communication skills for delivering constructive, learner-focused feedback.
  • Comfortable working in asynchronous learning environments and using digital platforms.
  • Adaptability in managing multiple grading tasks within deadlines.

Pay Range Disclosure
The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.
Equal Opportunity Statement
Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").

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