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Computational Data Analytics Jobs in California (NOW HIRING)

CarParts.com

Data Analyst

Long Beach, CA · On-site

$90K/yr

... computational approaches. As part of the Data Science team, you will contribute to ETL design ... Design and optimize ETL pipelines for reporting and analytics. * Apply strong coding skills and ...

Toyon

Computational Multiphysics Engineer

Goleta, CA

$125K - $195K/yr

We are seeking a Computational Multiphysics Engineer with expertise in numerical methods and ... Strong programming skills in Python, MATLAB, or C++ for simulation automation and data analysis.

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Computational Data Analytics information

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$24

$54

$93

How much do computational data analytics jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for computational data analytics in California is $54.03, according to ZipRecruiter salary data. Most workers in this role earn between $43.41 and $61.20 per hour, depending on experience, location, and employer.

How does a computational data analyst typically collaborate with cross-functional teams to deliver data-driven insights?

Computational Data Analysts frequently work alongside professionals from various departments, such as engineering, product management, and business strategy. They gather requirements, clarify analysis goals, and present findings in clear, actionable terms. Regular meetings and collaborative tools are often used to ensure alignment, while analysts translate complex data patterns into practical recommendations that support decision-making across the organization. This teamwork not only enhances the impact of their analyses but also provides valuable opportunities for learning and professional growth.

What are the key skills and qualifications needed to thrive as a computational data analytics professional, and why are they important?

To thrive as a Computational Data Analytics professional, you need strong quantitative skills, proficiency in statistics, and expertise in data manipulation, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, experience with data visualization tools (e.g., Tableau, Power BI), and knowledge of machine learning frameworks are commonly required. Excellent problem-solving abilities, effective communication, and the capacity to work collaboratively make candidates stand out. These skills enable professionals to extract actionable insights from complex datasets, drive informed decision-making, and add significant value to organizations.

What is the difference between Computational Data Analytics vs Data Scientist?

AspectComputational Data AnalyticsData Scientist
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fieldsBachelor's or Master's in Data Science, Computer Science, Statistics, or related fields
Work EnvironmentData analysis teams, research labs, tech companiesData analysis teams, research labs, tech companies
Employer & Industry UsageTech, finance, healthcare, academiaTech, finance, healthcare, academia
Common Search & ComparisonYesYes

Computational Data Analytics focuses on developing algorithms and computational methods to analyze large datasets, often emphasizing programming and algorithm design. Data Scientists combine statistical analysis, machine learning, and domain expertise to interpret data and generate insights. While both roles require similar educational backgrounds and work environments, Computational Data Analytics leans more toward algorithm development, whereas Data Scientists focus on modeling and interpretation.

What is computational data analytics?

Computational data analytics is the process of using computational methods, algorithms, and systems to analyze large and complex datasets. This field combines principles from computer science, mathematics, and statistics to extract meaningful insights and patterns from data. Professionals in computational data analytics use tools such as machine learning, data mining, and statistical modeling to solve real-world problems in various industries. Their work often involves programming, data visualization, and working with big data platforms.
What are popular job titles related to Computational Data Analytics jobs in California? For Computational Data Analytics jobs in California, the most frequently searched job titles are:
What job categories do people searching Computational Data Analytics jobs in California look for? The top searched job categories for Computational Data Analytics jobs in California are:
Computational Data Analytics jobs near you
Infographic showing various Computational Data Analytics job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 2% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $112,382 per year, or $54 per hour.

Scientist 3 - Translational Medicine, Oncology

Genentech, Inc.

South San Francisco, CA • On-site

$100K - $186K/yr

Full-time

Posted 19 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

Genentech's Translational Medicine Oncology (TM ONC) Department supports the entire R&D portfolio of novel therapies. We develop and implement biomarker strategies to study disease pathways, confirm a therapeutic's mechanism of action, and improve clinical trial efficiency and success. Biomarker scientists within our department are responsible for conducting biomarker discovery, developing biomarker strategies, designing and implementing biomarker assays, and interpreting biomarker results. Additionally, we conduct foundational clinical translational research to study the molecular and cellular pathways driving disease to generate novel target and biomarker approaches.
The Opportunity
As a scientist in Translational Oncology, you will drive hands-on, lab-based translational research and discovery efforts in lung and gastrointestinal (GI) cancers. This is an exciting opportunity to contribute to one of the fastest-moving areas in oncology, where rapid advances in RAS-targeted therapies are transforming the treatment landscape and creating unprecedented opportunities for biomarker discovery and translational innovation. Working within a vibrant, highly collaborative environment alongside experts across Research Oncology, Computational Sciences, and Translational Genomics and Proteomics, you will bridge foundational science and clinical impact to accelerate new therapeutic strategies.
  • Drive Hypothesis Validation: Design and execute laboratory experiments to validate biological and therapeutic hypotheses derived from non-clinical, clinical, and real-world data.
  • Analyze High-Dimensional Data: Synthesize, analyze, and interpret experimental and computational data in close collaboration with functional domain experts.
  • Decipher Disease Mechanisms: Investigate the molecular mechanisms underlying disease progression, therapeutic response, and acquired resistance to targeted therapies (e.g., RAS inhibitors) to inform patient selection, pharmacodynamic biomarker assessment, and combination treatment strategies.
  • Innovate Assay Platforms: Identify, evaluate, and validate innovative cell-based, biochemical, and multi-omic assays, including single-cell and functional genomics technologies, to enable scalable hypothesis testing.
  • Build Strategic Partnerships: Proactively establish strategic research collaborations to access emerging technologies, datasets, and analytical methods that fuel translational innovation.
  • Collaborate for Impact: Partner seamlessly across multi-disciplinary teams to translate scientific insights into meaningful therapeutic opportunities for patients.

Who You Are
You are a dedicated, curious scientist with a creative and rigorous approach to experimental design and problem-solving. You thrive in a fast-paced, collaborative team culture where diverse perspectives drive innovation.
  • Education & Experience: Ph.D. in Cancer Biology, Cell Biology, Molecular Biology, Genetics & Genomics, or a related discipline (or a Bachelor's degree with 6+ years / Master's degree with 4+ years of relevant research experience).
  • Scientific Expertise: Deep understanding of cancer biology, mechanisms of action and resistance to targeted therapies, and oncogenic signaling pathways (e.g., RAS/MAPK), alongside foundational knowledge of cancer immunology and the tumor microenvironment.
  • Technical Proficiency: Demonstrated ability to independently lead laboratory research using methods such as genome editing, genetic/chemical perturbation screening, cell-based/biochemical assays, cell culture and organoid models, flow cytometry, spatial omics, or single-cell technologies.
  • Proven Track Record: Demonstrated scientific contributions through peer-reviewed publications, patents, or impactful research accomplishments.

Preferred:
  • Data Analysis Skills: Familiarity or proficiency with the computational analysis of high-throughput data (such as multi-omics, single-cell, or spatial transcriptomics datasets).

Together, we'll advance along the whole patient journey with the aspiration to prevent, stop and cure diseases.
  • Relocation benefits are not available for this posting.

The expected salary range for this position based on the primary location of California is $100,400 - $186,400. 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
#TMONC
Global Grade -
SE6
Please note that the global grade displayed is a target global grade for the role and the actual global grade offered to a candidate may vary depending on several factors - including scope and breadth of the role. For further information relating to global grading in Roche please visit the global grading gSite.
Roche is dedicated to ensuring fair and transparent pay practices for its employees. In compliance with state legal requirements, you may notice some of our job postings will now list salary ranges. Please note that the broad ranges are aligned with our global grading framework and, in some cases, may also include geographic differentials.
As you consider making a change within the organization, this can include not only roles and responsibilities, but also an impact to compensation and benefits. Please take time to review Employees on the Move gSite to understand more.
Roche is an equal opportunity employer.
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.

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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

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