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Data Science Software Engineer Jobs in California

Data Science Engineer

Livermore, CA · On-site

$134K - $161K/yr

Broad experience with Python programming and software development. * Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems.

Data Science Engineer

Livermore, CA · On-site

$134K - $161K/yr

Broad experience with Python programming and software development. * Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems. * Intermediate ...

Broad experience with Python programming and software development. * Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems. * Intermediate ...

Data Science Engineer

Livermore, CA · On-site

$121K - $154K/yr

Experience with Python programming and software development, including version control (Git ... Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a ...

Experience with Python programming and software development, including version control (Git ... Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a ...

Experience with Python programming and software development, including version control (Git ... Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a ...

Software Development Engineer - Data

Cupertino, CA · On-site

$141K - $169K/yr

... Science, Software Engineering, Data Science, or a related technical field OR Hands-on engineering experience and a demonstrable track record of building and maintaining production data systems are ...

Software Engineer

Santa Clara, CA · On-site

$226K - $227K/yr

Analyze specifications, communications, data points, and programming requirements gathered per ... degree in Computer Science, Software Engineering or a related field plus two (2) years of ...

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... software engineers. Not only do we offer a great team to work with, but we also offer you an ...

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... software engineers. Not only do we offer a great team to work with, but we also offer you an ...

At SpaceXAI, we are building AI systems that push the frontier of human knowledge and scientific ... As a Software Engineer on SpaceXAI's Data team, you will be responsible for developing applications ...

Software Engineer, Data

San Francisco, CA · On-site

$134K - $162K/yr

They are seeking a Software Engineer, Data to design and maintain critical data pipelines that ... Responsibilities : • Work across our engineering organization and stakeholders from data science ...

Bachelor's degree in computer science, data science, engineering, math, physics, or scientific discipline; OR 2+ years of professional experience building software in lieu of a degree * 1+ years of ...

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Data Science Software Engineer information

See California salary details

$43.9K

$128K

$175.2K

How much do data science software engineer jobs pay per year?

As of Aug 2, 2026, the average yearly pay for data science software engineer in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Science Software Engineer, you need strong proficiency in programming (especially Python or R), a solid understanding of statistics and algorithms, and typically a degree in computer science, data science, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), data processing tools (like Spark or Hadoop), and cloud platforms (AWS, GCP, or Azure) is essential, as are relevant certifications. Excellent problem-solving abilities, communication skills, and the ability to work collaboratively with cross-functional teams set top performers apart. These competencies are vital for efficiently developing scalable data-driven solutions that drive business insights and innovation.

How does a Data Science Software Engineer typically collaborate with data scientists and other stakeholders on projects?

Data Science Software Engineers play a vital role in bridging the gap between data science and software engineering teams. They work closely with data scientists to translate prototypes and models into scalable, production-ready code, and often collaborate with product managers, analysts, and infrastructure engineers to ensure seamless integration. Regular communication and code reviews are essential, as is an iterative development process to address feedback and ensure solutions meet both technical and business requirements. This cross-functional collaboration helps deliver robust data-driven applications that align with organizational goals.

Which is the hardest field in it?

For a Data Science Software Engineer, the most challenging fields often involve complex machine learning algorithms, large-scale data processing, and advanced statistical analysis. Staying current with rapidly evolving tools like Python, R, and cloud platforms also requires continuous learning and adaptation. These areas demand strong problem-solving skills and deep technical knowledge.

What is a Data Science Software Engineer?

A Data Science Software Engineer is a professional who combines software engineering skills with data science expertise to build scalable data-driven systems and applications. They design, develop, and optimize software that supports data pipelines, machine learning models, and analytics platforms. Their work bridges the gap between data scientists, who focus on statistical analysis and modeling, and traditional software engineers, who focus on building robust and efficient software systems. Data Science Software Engineers ensure that data solutions are production-ready, scalable, and maintainable.

Can a software engineer work as a data scientist?

A software engineer can transition to a data scientist role by developing skills in statistics, machine learning, and data analysis, often using tools like Python, R, and SQL. While the roles have different focuses, software engineers' programming expertise can be a strong foundation for data science work, especially with additional training or experience in data modeling and analytics.

Is 40 too late for data science?

Data science software engineers can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is not a barrier if you develop the necessary technical expertise and stay current with industry trends.

What engineers make $500,000?

Senior data science software engineers with extensive experience, advanced skills in machine learning, and proficiency in tools like Python, R, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What is the difference between Data Science Software Engineer vs Data Analyst?

AspectData Science Software EngineerData Analyst
Required SkillsProgramming, software development, machine learningData visualization, statistical analysis, reporting
Work EnvironmentSoftware development teams, engineering projectsBusiness units, reporting teams
Common ToolsPython, Java, SQL, ML frameworksExcel, Tableau, SQL, R
Industry UsageTech, finance, healthcare, startupsMarketing, finance, retail, research

While both roles analyze data, Data Science Software Engineers focus on developing software solutions and machine learning models, requiring strong programming skills. Data Analysts primarily interpret data through visualization and statistical methods to support business decisions. The roles often overlap but serve different functions within organizations.

What are popular job titles related to Data Science Software Engineer jobs in California? For Data Science Software Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Science Software Engineer jobs in California look for? The top searched job categories for Data Science Software Engineer jobs in California are:
Infographic showing various Data Science Software Engineer 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, with an average salary of $128,018 per year, or $61.5 per hour.

Data Science Engineer

LLNL

Livermore, CA • On-site

$134K - $161K/yr

Full-time

Retirement

Re-posted 14 days ago


Job description

Company Description
Join us and make YOUR mark on the World!
Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.
Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.
Job Description
Wehave multiple openings for aData Science Engineer with a background in applied machine learning and data science for cybersecurity and power systems applications. You will design, build, and deploy novel data science capabilities to enhance the reliability and adversarial resilience of critical infrastructure. You will write code, create analytical tools and visualizations, diagnose complex systems, and discover innovative approaches to challenging problems. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate, in support of Global Security's Energy and Homeland Security (E) program.
Depending on your assignment, these positions may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.
These positions will be filled at eitherlevel based on knowledge and related experience as assessed by the responsibilities (outlined below) will be assigned if hired at the higher level.
You will
  • Design, develop, and apply machine learning and data science algorithms, including deep learning and modern AI techniques such as neural networks, transformers, and generative models, to analyze cybersecurity and power systems data.
  • Analyze data and build analytical capabilities to improve the reliability and adversarial resilience of critical infrastructure.
  • Write code to implement and deploy data science solutions and analytical tools, create visualizations, and follow software engineering best practices for code quality, testing, and documentation.
  • Collaborate with multidisciplinary teams including cybersecurity experts, power systems engineers, and computer scientists.
  • Support building research prototypes and capabilities for critical infrastructure protection, contributing to the development of new methodologies and tools.
  • Provide solutions to moderately complex to complex data analytics challenges in the cybersecurity and power systems domains, using established and innovative methods.
  • Perform other duties as assigned.

Additional job responsibilities, at the SES.3 level
  • Lead highly complex projects with technical and analytic challenges, developing innovative solutions and building advanced capabilities.
  • Discover and pioneer new approaches to data science problems, pushing the boundaries of current methodologies, and transforming ideas from concepts to operational solutions.
  • Present technical work and results to sponsors and technical audiences on a regular basis, demonstrating capabilities through hands-on demonstrations and deep technical discussions.
  • Contribute to technical direction and strategy for data science capabilities in critical infrastructure protection by building proof-of-concept systems, demonstrating new approaches, and contributing ideas to research proposals.

Qualifications
  • Ability to secureand maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
  • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field, or the equivalent combination of education and related experience.
  • Broad experience with Python programming and software development.
  • Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems.
  • Intermediateknowledge of software engineering best practices including version control, unit testing, and documentation.
  • Proficient verbal and written communication skills necessary to collaborate within a team environment and present technical information to varied audiences.
  • Effective interpersonal skills and initiative necessary to interact with all levels of personnel and work independently in a collaborative, multidisciplinary team environment.
  • Demonstrated ability to balance multiple projects and prioritize competing demands while maintaining high-quality standards for deliverables.

Additional qualifications at the SES.3 level
  • Advanced experience in applied machine learning and data science with demonstrated ability to deliver complex technical solutions independently.
  • Advanced experience building innovative data science systems and discovering novel approaches to complex problems.
  • Experience presenting technical work and demonstrations to both technical and non-technical audiences, including sponsors and stakeholders.

Qualifications We Desire
  • Master's degree or PhDin Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field.
  • Experience with modern machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, and/or similar tools.
  • Experience with deep learning techniques, transformer models, retrieval-augmented generation (RAG), fine-tuning pre-trained models, or adapting foundation models for specific application domains.
  • Knowledge of cybersecurity principles and practices, including threat detection, anomaly detection, or security analytics.
  • Experience with power systems, SCADA systems, industrial control systems, or operational technology environments.
  • Experience with data visualization and effectively communicating analytical results to diverse audiences.

Pay Range
$146,340 - $222,564 Annually
$146,340 - $185,544 Annually for the SES.2 level
$175,530 - $222,564 Annually for the SES.3 level
This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage.An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
Additional Information
#LI-Hybrid
Position Information
This is a Career Indefinite position, open to Lab employees and external candidates.
Why Lawrence Livermore National Laboratory?
  • Included in 2026Best Places to Work by Glassdoor!
  • Flexible Benefits Package
  • 401(k)
  • Relocation Assistance
  • Education Reimbursement Program
  • Flexible schedules (*depending on project needs)
  • Our values - visit https://www.llnl.gov/inclusion/our-values

Security Clearance
This position requires a Department of Energy (DOE) Q-level clearance.If you are selected, wewill initiate a Federal background investigation to determine if youmeet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship.
Pre-Employment Drug Test
External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Wireless and Medical Devices
Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the useand/or possession ofmobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area whereyou are not permitted to have a personal and/or laboratory mobile devicein your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.
Ifyou useamedical device, whichpairs with a mobile device,you must still follow the rules concerningthe mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities requireseparate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.
How to identify fake job advertisements
Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under "Find Your Job" of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.
To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf
Equal Employment Opportunity
We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.
Reasonable Accommodation
Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request.
CaliforniaPrivacy Notice
The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitlesjob applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here .