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Vice President Data Science Jobs in San Ramon, CA

About the Role We are seeking an experienced and highly strategic VP/SVP of Drug Discovery to lead ... Serve as a hands‑on scientific leader actively involved in experimental strategy, data ...

VP, Sales

Fremont, CA · On-site

$180 - $250/hr

Title: VP/SVP of Business Company: Mattson Technology, Inc. a 38-year Silicon Valley company ... data-backed optimizations to enhance offtake. * Accountable for delivering sustained growth of ...

Applied Data Science Summer Internship About Us: Evolver is a rapidly growing enterprise AI company ... and the former VP of AI from Microsoft, alongside senior leaders from other major global ...

Applied Data Science Summer Internship About Us: Evolver is a rapidly growing enterprise AI company ... and the former VP of AI from Microsoft, alongside senior leaders from other major global ...

You'll be a player-coach: collaborating directly with the founders and the science team to oversee ... Make key decisions on system design, cloud infrastructure, data pipelines, and our security and ...

Showing results 41-60

Vice President Data Science information

See San Ramon, CA salary details

$48.6K

$176K

$310.1K

How much do vice president data science jobs pay per year?

As of Aug 8, 2026, the average yearly pay for vice president data science in San Ramon, CA is $176,045.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,500.00 and $212,300.00 per year, depending on experience, location, and employer.

What are some common challenges faced by a vice president of data science when scaling data teams across an organization?

A Vice President of Data Science often encounters challenges such as aligning data initiatives with business objectives, ensuring consistent data governance practices, and fostering effective collaboration between technical and non-technical teams. Balancing the need for rapid innovation with maintaining data quality and compliance can also be demanding. Additionally, scaling the team requires strong leadership skills to recruit, mentor, and retain top talent while promoting a culture of knowledge sharing and continuous learning.

What is the difference between Vice President Data Science vs Data Scientist?

AspectVice President Data ScienceData Scientist
Required CredentialsAdvanced degrees (Master's/PhD), leadership experienceBachelor's or Master's in relevant field
Work EnvironmentExecutive leadership, strategic planningTechnical analysis, model development
Employer & Industry UsageCorporate, large organizations, tech, financeVaried industries, research labs, startups

The Vice President Data Science typically oversees data strategy and manages teams, requiring leadership and strategic skills. Data Scientists focus on building models and analyzing data. While both roles require strong technical skills, the VP role emphasizes management and vision, whereas Data Scientists are more hands-on with data analysis.

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

To thrive as a Vice President of Data Science, you need deep expertise in statistics, machine learning, and data analytics, typically supported by an advanced degree in a quantitative field and significant leadership experience. Familiarity with data platforms like Hadoop, Spark, and cloud-based analytics tools, as well as experience with programming languages such as Python or R, is crucial, along with certifications in data management or analytics. Strong strategic vision, communication, and team leadership skills distinguish top performers in this role. These skills and qualities drive innovation, enable data-driven decision-making, and ensure alignment with organizational goals.

What does a vice president of data science do?

A Vice President of Data Science leads the data science division within an organization, overseeing teams that analyze large datasets to drive strategic business decisions. They are responsible for developing data-driven strategies, managing data science projects, and ensuring the alignment of analytics initiatives with the company’s goals. This executive role also involves collaborating with other leaders, mentoring data science teams, and staying updated on the latest technologies and trends in data science. Ultimately, the Vice President of Data Science ensures that the organization's data assets are leveraged to create measurable business value.

What does a vice president of data science do?

As vice president of data science, your responsibilities include targeting audiences through both online and offline data. You lead a team of analysts, manage client needs, and implement solutions to build brands. Predictive analytics is a large part of this job, as is the ability to create strong content based on data science. You use analytical data to develop a business model that reaches a broader audience. Other duties include providing thought leadership, anticipating project risks, and translating analytical science into actionable marketing campaigns. This role is almost always in-house.

What are the most commonly searched types of Data Science jobs in San Ramon, CA? The most popular types of Data Science jobs in San Ramon, CA are:
What job categories do people searching Vice President Data Science jobs in San Ramon, CA look for? The top searched job categories for Vice President Data Science jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Vice President Data Science jobs? Cities near San Ramon, CA with the most Vice President Data Science job openings:
Infographic showing various Vice President Data Science job openings in San Ramon, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $176,045 per year, or $84.6 per hour.

VP/SVP of Drug Discovery

Deep Origin

San Francisco, CA • On-site

$200 - $300/hr

Other

Medical, Dental, Vision

Re-posted 7 days ago


Job description

About the Company

Deep Origin is building an operating system for science that transforms how life science research is conducted. Led by Michael Antonov, co-founder of Oculus, and backed by Formic Ventures, we are redefining the infrastructure behind modern drug discovery.

We are now building the next-generation platform for predicting drug toxicity in silico, transforming how pharmaceutical companies evaluate safety before clinical trials. Our mission is to reduce failure rates, accelerate drug development, and eliminate unnecessary animal testing through high-fidelity computational models of human biology.

We are not building incremental QSAR tools. We are building foundational infrastructure for predictive toxicology in the age of AI, systems biology, and large-scale computation.

About the Role

We are seeking an experienced and highly strategic VP/SVP of Drug Discovery to lead and scale our discovery organization across target identification, hit discovery, lead optimization, translational strategy, and clinical transition.

This is a critical executive leadership role for a hands‑on scientific leader who has spent significant time navigating the realities of drug discovery and development — someone who understands not only what can work scientifically, but what actually translates into successful therapeutic programs.

This individual will serve as a key scientific and operational leader inside the company, partnering closely with computational scientists, experimental scientists (own lab), platform teams, translational biology, external collaborators, and executive leadership to prioritize programs, guide strategic decisions, and accelerate pipeline execution.

This is not a purely managerial role. We are looking for someone who remains deeply engaged in scientific reasoning, program review, experimental strategy, and portfolio decision‑making.

The role is ideal for a senior biotech leader who wants to help build a next‑generation AI‑enabled discovery organization from the ground up while directly influencing the future direction of therapeutic development.

Requirements
  • PhD, MD, or equivalent advanced scientific degree in biology, pharmacology, chemistry, immunology, translational medicine, or related field
  • 15+ years of experience in drug discovery and development within biotech, mid‑size biotech, platform biotech, and/or pharmaceutical environments
  • Significant leadership experience in discovery organizations, including VP, SVP, CSO, CEO, or equivalent leadership roles
  • Proven experience building, scaling, and leading multidisciplinary discovery teams, including managing senior scientific leaders rather than only operating as an individual hands‑on contributor
  • Proven track record advancing therapeutic programs from early discovery through IND‑enabling development and/or into the clinic
  • Deep understanding of translational strategy, preclinical development, and clinical considerations in drug development
  • Experience working closely with clinical development teams and supporting programs through clinical transition
  • Strong expertise across multiple drug discovery modalities and approaches, with demonstrated ability to apply strategic scientific judgment
  • Experience leading cross‑functional and multidisciplinary discovery teams
  • Strong operational mindset with the ability to execute effectively in fast‑moving, resource‑constrained environments
  • Excellent communication and stakeholder management skills across scientific, executive, and external audiences.
Preferred Qualifications
  • Experience in AI‑enabled drug discovery, computational biology, systems pharmacology, or platform biotech environments
  • Background working with data‑driven discovery approaches and computational infrastructure
  • Experience across multiple therapeutic areas and modalities
  • Familiarity with translational biomarkers, precision medicine strategies, and clinical development planning
  • Experience building discovery organizations or scaling R&D teams within startup environments
  • Prior experience interacting with regulatory agencies, KOLs, or strategic pharma partnerships
  • Entrepreneurial or venture‑backed biotech experience strongly preferred.
Key Responsibilities
  • Lead and oversee therapeutic discovery programs from target identification through preclinical development and clinical transition
  • Drive scientific strategy, portfolio prioritization, and stage‑gate decision‑making across discovery programs
  • Partner closely with translational and clinical teams to ensure strong alignment between discovery strategy and clinical development pathways
  • Apply deep drug discovery experience to evaluate program risk, mechanism validity, biomarker strategy, developability, and probability of technical and clinical success
  • Build and lead multidisciplinary teams spanning biology, chemistry, pharmacology, translational medicine, computational biology, and external collaborators
  • Serve as a hands‑on scientific leader actively involved in experimental strategy, data interpretation, candidate selection, and program execution
  • Help establish scalable discovery and development processes appropriate for a high‑growth biotech environment
  • Contribute to corporate strategy, investor discussions, partnering opportunities, and scientific positioning
  • Evaluate and integrate emerging technologies, external innovation, and AI‑enabled methodologies into discovery workflows where appropriate
  • Mentor scientific leaders and help cultivate a culture of scientific rigor, urgency, accountability, and innovation.
Values & Working Style
  • Comfortable navigating ambiguity in a fast‑moving, high‑impact environment
  • Strong collaborator across science, engineering, and business teams
  • Pragmatic yet ambitious — focused on building category‑defining systems, not incremental improvements.
Why This Role Matters Now

Deep Origin is entering a phase where scientific innovation, platform infrastructure, and commercial partnerships must scale simultaneously.

This role will help shape how we translate cutting‑edge computational capabilities into real drug discovery outcomes — guiding portfolio decisions, advancing programs toward the clinic, and building the foundation of a next‑generation discovery organization.

Benefits
  • Opportunity to define the future of drug safety and predictive toxicology
  • Competitive compensation package with meaningful equity
  • Comprehensive health, dental, and vision coverage
  • Remote‑friendly culture with optional onsite work
  • Annual team gatherings and company events.
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