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Data Science Project Manager Jobs in Boston, MA (NOW HIRING)

CarGurus

Manager, Data Science

Boston, MA

Role overview The Manager, Data Science will lead an Inventory & Dealer Data Science team focused ... projects and aligning them with business goals. * Knowledge of standard software development ...

CarGurus

Manager, Data Science

Boston, MA · On-site

Role overview The Manager, Data Science will lead an Inventory & Dealer Data Science team focused ... projects and aligning them with business goals. * Knowledge of standard software development ...

Fidelity Investments

Director, Data Science

Boston, MA · On-site

$126K/yr

Excellent planning, project management, leadership, and research skills * Experience communicating ... a data science team within the Quantitative Research and Investment Technology division in the ...

Fidelity Investments

Director, Data Science

Boston, MA · On-site +1

$126K/yr

Excellent planning, project management, leadership, and research skills * Experience communicating ... a data science team within the Quantitative Research and Investment Technology division in the ...

RUE GILT GROUPE

Senior Data Scientist

Boston, MA · On-site

Work on challenging data science projects including Generative AI, NLP, image recognition ... Lead and manage large-scale, cross-functional projects from conception through completion, engaging ...

RUE GILT GROUPE

Senior Data Scientist

Boston, MA · On-site +1

Work on challenging data science projects including Generative AI, NLP, image recognition ... Responsible for designing, executing, and managing advanced A/B testing frameworks, including the ...

Jj

Manager, Data Science - Oncology

Cambridge, MA · On-site +1

The Manager, Data Science - Oncology will support how we advance data capture, build and optimize ... This role will focus on applications in Oncology R&D and support data projects from across the ...

Lutron Electronics

Data Scientist

Boston, MA · On-site

Responsibilities : • Contribute to end-to-end data science projects that improve product performance, customer experience, and operational efficiency, applying your strong analytical thinking and ...

Formation Bio

Director, Data Science

Boston, MA · On-site

$235K - $307K/yr

Lead and execute complex data science projects that directly advance our drug development portfolio * Develop and implement sophisticated models for therapeutic hypothesis evaluation, including ...

Varsity Tutors

Data Science Tutor

Waltham, MA · Remote

$40/hr

... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ... Adapts instruction using Jupyter notebooks, real-world data sets, and end-to-end project workflows ...

Lutron Electronics Co., Inc

Data Scientist

Boston, MA · On-site

$120K/yr

... managers, and business partners to turn data into actionable insights and deploy models into production. Responsibilities * Contribute to end-to-end data science projects that improve product ...

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Data Science Project Manager information

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How much do data science project manager jobs pay per hour?

As of May 31, 2026, the average hourly pay for data science project manager in Boston, MA is $62.56, according to ZipRecruiter salary data. Most workers in this role earn between $54.13 and $73.22 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Project Manager, and why are they important?

To thrive as a Data Science Project Manager, you need a solid understanding of data science methodologies, project management principles, and usually a degree in computer science, statistics, or a related field. Familiarity with analytics tools (such as Python, R, SQL), project management software (like Jira or Trello), and certifications such as PMP or Agile/Scrum are often required. Strong leadership, communication, and problem-solving skills set top performers apart by enabling effective team coordination and stakeholder management. These competencies ensure projects are delivered on time, within scope, and generate actionable insights that drive business value.

How does a Data Science Project Manager typically collaborate with data scientists and stakeholders throughout a project?

A Data Science Project Manager acts as a bridge between technical teams and business stakeholders, ensuring clear communication of goals, timelines, and deliverables. They facilitate regular meetings to discuss project progress, address any obstacles, and realign priorities as needed. By translating business requirements into actionable tasks for data scientists and providing updates to stakeholders, they help ensure that projects stay on track and deliver value. Effective collaboration often involves balancing technical feasibility with business needs, managing expectations, and fostering a cooperative team environment.

What is a Data Science Project Manager?

A Data Science Project Manager is a professional who oversees and coordinates data science projects from inception to completion. They act as a bridge between technical data science teams and business stakeholders, ensuring that project goals align with organizational objectives. Responsibilities include planning project timelines, managing resources, mitigating risks, and communicating progress. They also help define project requirements, monitor deliverables, and ensure that outcomes meet quality standards. Strong communication, analytical, and organizational skills are essential for this role.

What is the difference between Data Science Project Manager vs Data Analyst?

AspectData Science Project ManagerData Analyst
Required CredentialsOften requires a bachelor’s or master’s in data science, analytics, or related fields; project management certifications beneficialTypically holds a bachelor’s degree in statistics, mathematics, or related areas; certifications like Microsoft Excel or Tableau are common
Work EnvironmentLeads data science projects, collaborates with data scientists, engineers, and stakeholdersAnalyzes data sets, creates reports, visualizations, and supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms managing data science initiativesFound across industries for data reporting, business intelligence, and operational analysis

In summary, a Data Science Project Manager oversees data science projects and manages teams, requiring project management skills and relevant certifications. A Data Analyst focuses on analyzing data and creating reports, with a more technical and analytical role. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

What are popular job titles related to Data Science Project Manager jobs in Boston, MA? For Data Science Project Manager jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Data Science Project Manager jobs in Boston, MA look for? The top searched job categories for Data Science Project Manager jobs in Boston, MA are:
Data Science Project Manager jobs near you
Manager, Data Science

Manager, Data Science

CarGurus

Boston, MA

Other

Posted 23 days ago

Job description

Role overview

The Manager, Data Science will lead an Inventory & Dealer Data Science team focused on developing, deploying, and optimizing machine learning models that power CarGurus' products and business insights. Sitting within the broader Data Science organization, this team is responsible for modeling automotive marketplace dynamics and dealer behavior. The team owns Machine Learning solutions end-to-end across the ML lifecycle, from R&D to production. This leader is accountable for the team's strategic direction and impactful delivery, while building a culture of innovation, technical excellence, and collaboration. The Manager partners with Product, Engineering, Analytics, and cross-functional stakeholders to ensure team efforts advance CarGurus' goals in intelligence-powered products.

What you'll do

  • Oversee the development, training, and evaluation of machine learning models covering Inventory and Dealer intelligence. Leverage modeling techniques including recommendations, demand forecasting, churn risk prediction, and valuation algorithms.
  • Facilitate experimentation, A/B testing, and measurement of production models, ensuring robust evaluation of business impact
  • Build and develop a high-performing team - providing regular coaching, feedback, and performance assessments; ensure equitable access to growth opportunities.
  • Drive innovation, continuous improvement, and adoption of best-in-class ML and AI practices. Champion best practices across the organization.
  • Participate in roadmap planning, aligning the team's work with broader business priorities and long-term strategy. Flag resource constraints and escalate tradeoff decisions when needed.
  • Act as a visible, accessible leader - communicating objectives, updates, risks, and wins to all stakeholders.
  • Partner with peers in the Machine Learning Platform, Product and Data teams, and other stakeholders to facilitate effective cross-team working relationships and represent data science in cross-functional forums.

What you'll bring

  • 5+ years of experience in a data science or machine learning engineering role
  • 2+ years of people leadership experience
  • Deep expertise in machine learning models and their application to classification, regression, ranking, and recommendation problems. Familiarity with standard evaluation metrics and statistical best practices.
  • Experience deploying and owning models in production and a working understanding of MLOps practices.
  • Strong working knowledge of Python development best practices and the Python ML ecosystem (e.g., scikit-learn, PyTorch, XGBoost, numpy, pandas).
  • Experience with cloud platforms, particularly AWS, including deploying, monitoring, and troubleshooting ML models.
  • Effective communication and facilitation abilities with both technical and non-technical stakeholders (including data scientists, product management, senior leadership, and engineers).
  • Experience contributing to the technical direction for a team and a strategic mindset for prioritizing projects and aligning them with business goals.
  • Knowledge of standard software development methodologies and a history of driving continuous improvement.
  • Experience in a collaborative, cross-functional environment, with the ability to build effective working relationships and foster an inclusive team culture.

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