1

Manager Of Data Science Jobs (NOW HIRING)

We are tackling one of the world's most important infrastructure challenges: helping the energy ... As a Data Science Manager, you will act as a pivotal technical leader to bridge the gap between ...

Manager of Data Engineering

New York, NY · On-site

$200K - $220K/yr

Manager of Data Engineering ID: 1038 Location: Brooklyn, NY More about this job > Description Moda Operandi is seeking a hands-on Manager of Data Engineering to lead the data engineering function ...

Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent ... We're looking for a Data Science Manager to lead our growing AI product data science function. This ...

Data Science Manager

Los Angeles, CA · On-site

$160K - $220K/yr

Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent ... We're looking for a Data Science Manager to lead our growing AI product data science function. This ...

Data Science Manager

$160K - $170K/yr

Covering 40% of all U.S. transactions and active in 45 countries , Appriss Retail is trusted by 60 ... Overview The Data Science Manager is a player-coach who leads a small, high-output team while ...

Sr Manager, Data Science

Woonsocket, RI · On-site +1

$140K - $260K/yr

We're building a world of health around every individual - shaping a more connected, convenient and ... Directs activities of data scientists, providing guidance, mentorship, and performance management ...

Job Summary : 1872 Consulting is a company specializing in data science and analytics, and they are seeking a Data Science Manager to lead a team of data scientists. The role involves designing and ...

... management and application development pipeline in support of national defense data science and data architecture prototyping tasks. This role will also include gathering and organizing data ...

Lead and develop a team of data scientists responsible for high-impact analytics, predictive ... You have experience managing and developing data scientists or analysts and know how to set a high ...

... Data Science Manager for our Sports Modeling & Innovation team to tackle our most challenging ... Throughout the lifecycle of a model, from data collection through results, you will create ...

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of ...

Showing results 21-40

Manager Of Data Science information

See salary details

$31K

$97.1K

$172K

How much do manager of data science jobs pay per year?

As of Sep 6, 2026, the average yearly pay for manager of data science in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

What is a manager of data science?

A Manager of Data Science is a leadership role responsible for overseeing a team of data scientists and analysts, guiding data-driven projects, and ensuring that business objectives are met through data analysis and modeling. They collaborate with stakeholders to identify business needs, design analytical solutions, and manage the end-to-end process of extracting insights from large datasets. In addition to technical expertise, this role requires strong leadership, project management, and communication skills to translate complex findings into actionable strategies.

How does a manager of data science typically balance hands-on technical work with team leadership responsibilities?

A Manager of Data Science often divides their time between overseeing project execution and supporting their team's professional growth. While they may still participate in high-level technical decision-making and occasionally contribute to code or modeling, much of their focus shifts to setting strategic direction, mentoring team members, and facilitating cross-functional collaboration. They are responsible for ensuring that projects align with business goals, providing technical guidance, and creating an environment where data scientists can thrive. Effective managers also spend time communicating with stakeholders to translate business needs into actionable data projects.

What are the key skills and qualifications needed to thrive as a manager of data science, and why are they important?

To thrive as a Manager of Data Science, you need advanced expertise in data analytics, machine learning, and statistical modeling, typically backed by a degree in a quantitative field and prior experience in data science roles. Familiarity with tools like Python, R, SQL, cloud platforms (e.g., AWS, Azure), and project management systems is essential, and certifications such as Certified Analytics Professional (CAP) can be valuable. Strong leadership, communication, and problem-solving skills help in guiding teams, translating business needs into data solutions, and fostering collaboration. These skills and qualities are crucial for delivering actionable insights, driving innovation, and ensuring successful data-driven strategies in complex organizational environments.

What is the difference between Manager Of Data Science vs Data Scientist?

AspectManager Of Data ScienceData Scientist
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; often leadership experienceBachelor's or Master's in Data Science, Statistics, or related field; strong technical skills
Work EnvironmentOversees teams, manages projects, collaborates with stakeholdersFocuses on data analysis, model development, and technical problem-solving
Employer & Industry UsageUsed in organizations with data teams, analytics departmentsCommonly employed in tech, finance, healthcare, and research sectors

The main difference between a Manager Of Data Science and a Data Scientist is the level of responsibility. Managers oversee teams and strategic initiatives, while Data Scientists focus on technical data analysis and model building. Both roles require strong analytical skills, but the Manager role emphasizes leadership and project management.

What cities are hiring for Manager Of Data Science jobs?

Cities with the most Manager Of Data Science job openings:

What are the most commonly searched types of Of Data Science jobs?

The most popular types of Of Data Science jobs are:

Who are the top companies hiring for Manager Of Data Science jobs?

The top employers for Manager Of Data Science jobs are:

What states have the most Manager Of Data Science jobs?

States with the most job openings for Manager Of Data Science jobs include:

Data Science Manager

Tapestry

Mountain View, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 11 days ago


Tapestry Inc. rating

8.2

Company rating: 8.2 out of 10

Based on 36 frontline employees who took The Breakroom Quiz

1st of 105 rated fashion retailers


Job description

About Tapestry

Tapestry is a group within Google working to build the AI-powered electric grid. We are tackling one of the world's most important infrastructure challenges: helping the energy system become more visible, understandable, reliable, affordable, abundant, and clean.

Originally born at X, Alphabet's moonshot factory, Tapestry brings together experts in energy, AI, software engineering, and products to build tools that help the electricity ecosystem plan smarter, move faster, and operate more efficiently.

This is a global effort. Tapestry supports partners across the U.S., U.K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy future.

Joining Tapestry means doing high-impact work with a multidisciplinary team tackling a problem that matters at global scale. Learn more about our team and our mission here.

About the role:

At Tapestry, data drives all our decision-making. Data Scientists work across the organization to help shape our business and technical strategies by processing, analyzing, and interpreting massive datasets. They lead our metrics assessment, analyze massive datasets and derive early insights, and partner with cross functional teams on the right datasets for maximum downstream impact. As a Data Science Manager, you will act as a pivotal technical leader to bridge the gap between complex business questions and advanced technical execution. You will build, mentor, and lead a high-performing team of data scientists to deliver operational excellence, accelerate product advancement, and drive business value.

In this role, you will deeply immerse yourself with the team of data scientists in data collection and analysis, develop compelling, synthesized recommendations for senior leadership, and be involved  to help drive implementation. Ultimately, your team's solutions will fundamentally improve electric grid visibility and resilience.

How you will contribute to the team...

1. Team Leadership and Strategic Delivery

  • People Management: Recruit, mentor, and lead a world-class team of data scientists. Cultivate talent through active technical mentorship and clear career development paths.
  • Cross-Functional Alignment: Collaborate with engineering, product, power system experts, and external partners to translate high-level business goals into rigorous data science roadmaps.
  • Executive Communication: Persuasively communicate your team's findings and strategic recommendations to senior executives and cross functional teams, tracking the long-term business impact of the solutions.

2. Data Integrity and Curation Strategy at Scale

  • Pipeline Oversight: Guide the team in discovering, investigating, and deriving insights from large and complex input datasets, both current and potential, from partners and other sources.
  • Gatekeeping Metrics: Oversee the definition of problem framing, test datasets, and core business, product and performance metrics that machine learning models will aim to optimize for.
  • Multi-Stage Quality Control: Ensure data integrity across the pipeline by establishing frameworks to assess intermediate datasets and metrics within multi-stage machine learning processes.
  • Annotation Rigor: Drive a comprehensive and scalable data annotation strategy that prioritizes quality through statistical rigor, ensuring data reliability for all downstream modeling.

3. Problem Definition and Advanced Analytics

  • Grid Visibility and Innovation: Lead the proactive exploration of new problem spaces to fundamentally improve electric grid visibility and resilience.
  • Experimentation Frameworks: Standardize how the team designs, executes, and analyzes A/B tests and other experiments to validate hypotheses and measure product impact.
  • Engineering Best Practices: Champion modern data science workflows, including the application of GenAI techniques for data analysis, ensuring the team follows robust engineering best practices.
What you should have...
  • PhD or Master's in a quantitative field and 8+ years of tech or energy industry work experience as a statistician, quantitative analyst, or data scientist. 
  • 5+ years of experience directly managing or leading high-performing data science and analytics teams, with a proven track record of delivering production-grade data solutions.
  • A proven track record of identifying where data science can add unique value during early product development, alongside a strong ability to influence other teams to collaborate on critical data science work.
  • Advanced skills in experimental design, including the ability to architect, guide, and validate robust A/B testing methodologies and statistical experiments in ambiguous environments.
  • Experience in Python, SQL, R, Pandas, Scikit-Learn, other ML frameworks as appropriate.
  • Experience with electric power grid data, and physics based understanding of electrical networks and utility data. Ability to bridge the gap between power systems and machine learning.
  • Experience in multivariate analysis, stochastic models, and sampling methods. Able to select the right statistical tool to solve for bias, variance, and data drift.
  • Applied experience with building comprehensive machine learning model evaluation tooling and processes on large datasets.
  • Proven ability to "zoom out" from complex technical details to build a cohesive product strategy, and "zoom in" to unblock technical hurdles.
  • Demonstrate strong collaboration with software engineering and cross functional teams to build ML-powered systems ready for production.
  • Exceptional storytelling abilities, with a knack for turning complex data pipelines and model metrics into clear business value for non-technical stakeholders.
Would be great to have...
  • Ability to thrive in ambiguity, set own goals and effectively delivering to them in a very fast-changing environment
  • Attention to detail, project management, and organizational skills
  • Fast learner with capacity to learn about a wide-spread of different technologies and industries
  • Passion for the energy and climate space
  • Track record of delivering scalable solutions to complex software problems
  • Experience in startup or high-growth environments

Tapestry Values:

  • Take charge: We take initiative and own outcomes that move the mission forward.
  • Transform with purpose: We build solutions that solve real problems and create meaningful impact.
  • Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
  • Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
  • Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.

What we offer:

A culture that supports growth, ownership, and meaningful impact, along with...

  • Competitive salary and equity
  • Medical, dental, and vision coverage
  • Generous PTO and flexible hybrid work model
  • 401(k) with employer contribution
  • Professional development
  • The ability to work on important real-world problems within an Alphabet-backed environment

The US base salary range for this full-time position is $207,000 - $304,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.


What Tapestry Inc. employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom