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Manager Of Data Science Jobs in California (NOW HIRING)

The data science team is very much applied - their work directly makes its way into real products ... a manger, and be directly responsible for some amount of the technical work in addition to ...

Data Science Manager

Irvine, CA · On-site

$119K - $197K/yr

The Manager Data Science is responsible for architecting, building, and deploying production-grade ... This is a highly technical, hands-on role that requires a combination of strong experience ...

Conduct experiments and statistical analysis to evaluate the effectiveness of business strategies. * Stay updated on industry trends and best practices regarding data science methodologies and ...

The Manager Data Science is responsible for architecting, building, and deploying production-grade ... This is a highly technical, hands-on role that requires a combination of strong experience ...

Leader of Data and Analytics

Auburn, CA · On-site

$118K - $140K/yr

... are data management, analytics or reporting. * Minimum 2 years of hands-on experience with Power BI. Demonstrated ability to develop interactive dashboards and reports. * Minimum 2 years of ...

... and managing the cutover process to ensure a smooth transition to the new system. The conversion is from Dynamics AX to SAP Responsibilities Development of Data Science Solutions: * Test and ...

Showing results 41-60

Manager Of Data Science information

See California salary details

$30.6K

$95.9K

$169.7K

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

As of Aug 16, 2026, the average yearly pay for manager of data science in California is $95,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,100.00 and $123,900.00 per year, depending on experience, location, and employer.

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.

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 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.

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

The most popular types of Of Data Science jobs in California are:

What cities in California are hiring for Manager Of Data Science jobs?

Cities in California with the most Manager Of Data Science job openings:

Data Scientist - Predictive Analytics, Senior

Pacific Gas and Electric Company

Oakland, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


Pacific Gas and Electric Company rating

9.0

Company rating: 9.0 out of 10

Based on 46 frontline employees who took The Breakroom Quiz

3rd of 53 rated energy and utility


Job description

Requisition ID # 169102
Job Category: Accounting / Finance
Job Level: Individual Contributor
Business Unit: Electric Engineering
Work Type: Hybrid
Job Location: Oakland
Department Overview
The System Performance, Reliability and Resiliency Strategy team within the overall Electric Transmission and Distribution Engineering organization is responsible for planning, organizing, and managing the resources necessary to successfully execute PG&E's Electric Reliability Strategy and initiatives. This team of forward-thinking individuals will be tasked with deploying technology and infrastructure and influencing the organization to achieve the company's reliability goals. The team is responsible for implementing programs required to modernize the electric grid allowing for safe, resilient and efficient operations. The team participates in a cross functional team of internal and consulting participants being tasked with leading the transition of a project from development and testing to being operational for each phase of each project.
Position Summary
Within the System Performance, Reliability and Resiliency Strategy team, this position reports to the Senior Manager of Reliability Analytics and is responsible for developing advanced data science models and industry-leading anomaly detection techniques to identify potential failures and enhance the reliability of the electric transmission and distribution grid.
Key responsibilities include designing, developing, and executing scripts, programs, models, algorithms, and processes using structured and unstructured data from diverse sources and of varying sizes. The goal is to generate defensible, valid, scalable, reproducible, and well-documented machine learning and artificial intelligence models (predictive or optimization) to support problem-solving and strategic decision-making.
The role also involves active participation in internal and external communities of practice in data science, AI, and machine learning to stay current and contribute to advancements in the field. Additionally, the candidate will help educate non-technical stakeholders on the benefits, limitations, and maturity of data science solutions.
In this role, the successful candidate will be uniquely positioned at the forefront of utility industry analytics. Working as part of cross-functional teams, including data engineers, data scientists, technologists, and subject matter experts - this individual will lead the development of data science capabilities that could lead to paradigm changes in how the utility operates.
  • This position is hybrid, working from your remote office and your assigned work location based on business need. The assigned work location will be within the PG&E Service Territory. Position requires reporting to Oakland/Dublin twice a week.

PG&E is providing the salary range that the company in good faith believes it might pay for this position at the time of the job posting. This compensation range is specific to the locality of the job. The actual salary paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, and internal equity. Although we estimate the successful candidate hired into this role will be placed towards the middle or entry point of the range, the decision will be made on a case-by-case basis related to these factors.
Bay Minimum: $126,000
Bay Maximum: $200,000
&/OR
CA Minimum: $120,000
CA Maximum: $190,000
This job is also eligible to participate in PG&E's discretionary incentive compensation programs.
Job Responsibilities
  • Lead research and development of state-of-the-art methodologies to detect potential system failures and improve the reliability of the electric transmission and distribution grid.
  • Applies data science/ machine learning /artificial intelligence methods to develop scalable, defensible and reproducible models,
  • Serves as the technical lead for the development of predictive/reliability analytics models.
  • Develops python codes for data processing and data science model developments (e.g., ML/AI models, advanced statistical models)
  • Documents datasets, modeling processes, and result to ensure transparency, reproducibility, and defensibility.
  • Contribute to the development of data science strategies aligned with system performance, reliability, and resiliency team goals.
  • Communicate technical concepts and model results to internal/external stakeholders.

Qualifications
Minimum:
  • Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field
  • 4 years in data science OR 2 years, if possess Master's Degree, as described above

Desired:
  • Ph.D. or Master's degree in Electrical Engineering, Mechanical Engineering, Operations Research, Transportation Engineering, Physics, Applied Sciences, Statistics, or a related field.
  • Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
  • Strong foundation in statistics, machine learning (ML), and artificial intelligence (AI).
  • Hands-on and theoretical experience in developing and deploying data science and ML models using Python.
  • Proven ability to formulate and solve unstructured, complex problems using data-driven approaches.
  • Proficiency in working with large datasets, including structured and unstructured data from diverse sources.
  • Excellent communication skills, with the ability to explain technical concepts to non-technical audiences.
  • Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies

Purpose, Virtues and Stands
Our Purpose explains "why" we exist:
  • Delivering for our hometowns
  • Serving our planet
  • Leading with love

Our Virtues capture "who" we need to be:
  • Trustworthy
  • Empathetic
  • Curious
  • Tenacious
  • Nimble
  • Owners

Our Stands are "what" we will achieve together:
  • Everyone and everything is always safe
  • Catastrophic wildfires shall stop
  • It is enjoyable to work with and for PG&E
  • Clean and resilient energy for all
  • Our work shall create prosperity for all customers and investors

More About Our Company
EEO
Pacific Gas and Electric Company is an Equal Employment Opportunity employer that actively pursues and hires a workforce that reflects the hometowns we serve. All qualified applicants will receive consideration for employment without regard to race, color, national origin, ancestry, sex, age, religion, physical or mental disability status, medical condition, protected veteran status, marital status, pregnancy, sexual orientation, gender, gender identity, gender expression, genetic information or any other factor that is not related to the job.
Employee Privacy Notice The California Consumer Privacy Act (CCPA) goes into effect on January 1, 2020. CCPA grants new and far-reaching privacy rights to all California residents. The law also entitles job applicants, employees and non-employee workers to be notified of what personal information PG&E collects and for what purpose. The Employee Privacy Notice can be accessed through the following link: Employee Privacy Notice
PG&E will consider qualified applicants with arrest and conviction records for employment in a manner consistent with all state and local laws.

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