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Head Data Science Jobs in California (NOW HIRING)

PROPRIUS

Director Data Science

San Francisco, CA

The head of this new Data Science division will be expected to solve classic e-commerce problems; targeted advertising and marketing, recommendation systems, behavioral analytics and customer ...

Adobe, Inc.

Sr. Manager, People Data Science

San Jose, CA · On-site

$161K - $303K/yr

This role will report to the Head of People Analytics and will lead a team of data scientists to derive insights and recommendations that inform strategic people-related decisions. What you'll Do ...

Adobe

Sr. Manager, People Data Science

San Jose, CA

$161K - $303K/yr

This role will report to the Head of People Analytics and will lead a team of data scientists to derive insights and recommendations that inform strategic people-related decisions. What you'll Do ...

AngelList

Head of Data

San Francisco, CA

About the Role We're hiring a Head of Data to turn AngelList's data into an unfair advantage ... For a growth-focused data scientist ready to do both, there aren't many roles like it.

AngelList

Head of Data

San Francisco, CA · On-site

About the Role We're hiring a Head of Data to turn AngelList's data into an unfair advantage ... For a growth-focused data scientist ready to do both, there aren't many roles like it.

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Head Data Science information

How to become head of data science?

To become a head of data science, professionals typically need extensive experience in data analysis, machine learning, and leadership roles, often requiring 8-10 years in data-related positions. A strong educational background in computer science, statistics, or related fields, along with skills in programming, data management, and strategic planning, is essential. Advanced degrees and certifications in data science or analytics can also enhance prospects for leadership positions.

Is 40 too late for data science?

The Head Data Science role and similar data science positions do not have strict age limits; many professionals transition into data science later in their careers. Success depends on relevant skills, experience, and continuous learning in areas like programming, statistics, and machine learning, regardless of age.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Chief Data Officer, Director of Data Science, or Lead Data Scientist, with salaries exceeding $150,000 annually and sometimes reaching over $200,000 for those with extensive experience, advanced skills in machine learning, and industry expertise. These roles typically require strong leadership, strategic thinking, and proficiency with tools like Python, R, and cloud platforms.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to optimize model performance and efficiency.

What does a Head of Data Science do?

A Head of Data Science is responsible for leading and managing the data science team within an organization. They oversee the development and implementation of data-driven strategies, ensuring that the team delivers valuable insights and predictive models to support business goals. This role involves collaborating with other departments, setting the vision for data initiatives, and ensuring best practices in data analysis and machine learning are followed. Additionally, the Head of Data Science often mentors team members and helps shape the organization's overall data strategy.

What are some common challenges faced by a Head of Data Science when building and leading a data science team?

As a Head of Data Science, one of the main challenges is balancing strategic leadership with hands-on technical guidance. You'll often need to align the team's goals with broader business objectives while ensuring that team members have the right mix of skills and resources. Additionally, fostering effective collaboration between data scientists, engineers, and business stakeholders can be complex, especially in cross-functional environments. Managing expectations around project timelines and communicating technical insights in a clear, actionable way are also key aspects of the role.

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

To thrive as a Head of Data Science, you need advanced expertise in statistics, machine learning, data modeling, and a strong background in computer science or a related quantitative field, often supported by a master's or Ph.D. Proficiency with programming languages like Python or R, big data platforms such as Hadoop or Spark, and familiarity with cloud-based analytics tools are typically required. Strategic leadership, excellent communication skills, and the ability to mentor and inspire teams are crucial soft skills for this role. These abilities are essential to drive data-driven decision-making, foster innovation, and align analytics initiatives with organizational goals.

What is the difference between Head Data Science vs Data Science Manager?

AspectHead Data ScienceData Science Manager
ResponsibilitiesStrategic leadership, setting data science vision, overseeing multiple teamsTeam management, project delivery, coordinating data science projects
Required SkillsAdvanced analytics, leadership, strategic planningTeam management, technical expertise, project management
ExperienceSenior data science background, leadership rolesData science experience with managerial responsibilities
Work EnvironmentExecutive level, cross-departmental collaborationTeam-focused, project-oriented

The Head Data Science typically holds a strategic, leadership role overseeing the entire data science function, while the Data Science Manager focuses on managing teams and project execution. Both roles require strong technical backgrounds, but the Head Data Science emphasizes vision and strategy, whereas the Data Science Manager concentrates on operational management.

What are the most commonly searched types of Data Science jobs in California? The most popular types of Data Science jobs in California are:
What cities in California are hiring for Head Data Science jobs? Cities in California with the most Head Data Science job openings:
Head Data Science jobs near you
Infographic showing various Head Data Science job openings in California as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.
Head, Innovation Accelerator Data Science

Head, Innovation Accelerator Data Science

Genentech, Inc.

South San Francisco, CA • On-site

Full-time

Posted 26 days ago

Genentech rating

8.8

Company rating: 8.8 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

11th of 86 rated pharmaceutical

Job description

A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche.
This role is based in the Innovation Accelerator (IA) team, the innovation engine and connective tissue for Design, Data and Data Science innovation strategy within Product Development Data Sciences (PDD). We translate our long-term PDD vision into actionable strategy, shaping and prioritizing innovative cross-functional use cases that span PDD, PD, and Pharma. As both integrators and incubators, we explore, prototype, and help productize solutions to deliver impact in close partnership with internal Roche teams and external collaborators. With a mindset rooted in openness, value creation, and adaptability, we navigate the innovation ecosystem to drive transformative impact and future readiness across the organization.
The Opportunity:
The Head of Innovation Accelerator Data Science is responsible for driving technical excellence across design, data and data science innovation programs for Roche Product Development. This role combines deep subject matter expertise in data science and software development with people leadership and portfolio oversight. The Head of IA Data Science ensures strong technical execution, guides architectural decisions, and aligns technical capacity with strategic goals. As a direct report to the Function Head, this position plays a critical role in shaping the innovation roadmap, scaling capabilities, and growing high-performing technical teams.
  • You provide technical leadership across early exploration and productization phases of innovation projects, ensuring alignment with departmental goals and enterprise direction
  • You act as subject matter expert and single point of escalation/problem resolution for applied data science and software engineering within the innovation portfolio
  • You influence PDD data, design and data science (3D) strategy and in-silico strategy & roadmap(s) through strategic technical leadership/expertise
  • You make architectural decisions independently and ensure adherence to best practices for scalability, performance, reliability, and compliance
  • You oversee execution quality, technical risk management, and project velocity across multiple high-impact workstreams and domains
  • You establish and enforce technical standards, enabling reuse, modularity, and robust design across solution development
  • You lead technical capacity planning and resource deployment within the team, prioritizing based on departmental strategy and portfolio needs
  • You collaborate with cross-functional and enterprise partners to translate innovation opportunities into feasible, impactful, and technically sound solutions
  • You drive the Innovation Accelerator portfolio through contribution to governance, resource planning, and progress reviews
  • You identify and integrate new technologies and platforms, applying functional expertise and organizational context to maximize department performance
  • You ensure traceability, reproducibility, and risk mitigation through robust documentation and engineering practices across all technical deliveries
  • You manage a multidisciplinary team of specialists and junior leaders (e.g., data scientists, software engineers), ensuring accountability for delivery, performance, and development
  • You oversee hiring, onboarding, workforce planning, and succession management aligned to departmental capabilities and strategic growth areas
  • You coach and mentor team members to enhance their individual performance and long-term potential, developing future technical leaders across roles and backgrounds
  • You foster a high-performance, inclusive culture focused on collaboration, ownership, and continuous improvement
  • You set development goals, conduct performance evaluations, and guide career progression based on business priorities and professional aspirations
  • You manage team deployment and resource allocation across a complex portfolio of innovation projects, balancing individual growth with business needs
  • You execute short-term department plans by managing priorities, budget, and capacity in coordination with function leadership
  • You influence senior stakeholders and functional leadership to secure alignment, resources, and sponsorship for technical priorities

Who you are:
  • You have an advanced degree (Master's or PhD) in Computer Science, Data Science, Statistics, Engineering, or a related technical field
  • You have 15+ years of hands-on experience in software engineering, data science, or technical innovation, ideally within R&D or regulated environments
  • You have 4+ years in a leadership role managing multidisciplinary technical teams
  • You have proven experience driving technology delivery from prototyping to scaled implementation
  • You have deep expertise in modern data and software development technologies and architectural practices
  • You are proficient with Python or R, and ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch
  • You have a strong understanding of supervised/unsupervised learning, statistical modeling, and experimental design
  • You are familiar with software development practices including version control, testing, and collaborative coding
  • You have experience running simulations or analyses in a high-performing computing environment
  • You have knowledge of and experience with four or more of the following:
    • Epidemiology, including causal inference methods for observational real world data (RWD) or real world evidence (RWE)
    • Bayesian statistics
    • Decision theory, including multiple criteria decision analysis (MCDA), utility elicitation, decision simulation models, or Value of Information
    • Clinical outcomes research using data from electronic health records (EHR)
    • Discovery mechanisms and evidence generation pathways for novel biomarkers and risk scores
    • Interpretable machine learning
    • Methods to incorporate knowledge graphs, ontologies, or other forms of structured information
    • Probabilistic programming languages
    • Complex or innovative clinical trial designs, including adaptive stopping, seamless Phase 2/Phase 3 designs
  • You have a strong track record in managing resources, planning capacity, and balancing competing priorities
  • You have excellent communication and stakeholder management skills
  • You are fluent in agile delivery, DevOps, or other modern ways of working
  • You have a passion for continuous learning
  • You have a passion for mentoring colleagues of all backgrounds
  • You have capacity for independent thinking and ability to make decisions based upon sound principles
  • You exhibit excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond technical domain
  • You demonstrate respect for cultural differences when interacting with colleagues in the global workplace
  • You possess excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language

Preferred:
  • Experience in pharma, life sciences, or healthtech sectors
  • Familiarity with regulated environments and compliance-driven product development
  • Exposure to innovation frameworks (e.g., lean startup, dual-track agile)
  • Demonstrated ability to assess and integrate emerging technologies (e.g., GenAI, ML Ops, cloud platforms)

Relocation benefits are not available for this posting
The expected salary range for this position based on the primary location of California is $254,400-$472,400. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
#PPDT
#PDDSSF
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

What Genentech employees say

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About Genentech

Sourced by ZipRecruiter

A member of the Roche Group, Genentech has been at the forefront of the biotechnology industry for more than 40 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech has multiple therapies on the market for cancer & other serious illnesses. Please take this opportunity to learn about Genentech where we believe that our employees are our most important asset & are dedicated to remaining a great place to work.

Industry

Scientific research and development services

Company size

10,000+ Employees

Headquarters location

South San Francisco, CA, US

Year founded

1976

Social media

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