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Computer Science Finance Jobs in California (NOW HIRING)

Bachelors degree in computer science, finance, accounting, business or related fields * In depth knowledge of accounting (or demonstrable experience of accounting processes) * Solid oral, written ...

Bachelors degree in computer science, finance, accounting, business or related fields * In depth knowledge of accounting (or demonstrable experience of accounting processes) * Solid oral, written ...

SAP GTS Functional Consultant - IC4

Mountain View, CA · On-site

$73.75 - $100.75/hr

Required Qualifications Bachelor's degree in Information Technology, Computer Science, Finance, or a related field. Master's degree preferred. Minimum of 7-10 years of experience in IT with a focus ...

Company Description Our team provides services to manage subscription based offers, integrating with financial, commerce and provisioning systems. We build the API layers for customer-facing user ...

Company Description Our team provides services to manage subscription based offers, integrating with financial, commerce and provisioning systems. We build the API layers for customer-facing user ...

S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ... Financial/ Telecommunication), powerbi/tableau, data warehouse Benefits * Competitive Salary * Paid ...

S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ... Financial/ Telecommunication), powerbi/tableau, data warehouse Benefits * Competitive Salary * Paid ...

Apply the principles and techniques of computer science, engineering, and mathematical analysis to ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Computer Engineer II

San Diego, CA · On-site

$113K - $133K/yr

Apply the principles and techniques of computer science, engineering, and mathematical analysis to ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Apply the principles and techniques of computer science, engineering, and mathematical analysis to ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Computer Engineer III

San Diego, CA · On-site

$113K - $133K/yr

Apply the principles and techniques of computer science, engineering, and mathematical analysis to ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

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Computer Repair Technician

Fremont, CA · On-site

$25.50 - $29.50/hr

... Computer Science or equivalent experience • Pays close attention to detail • Can work ... finance, hospitality, human resources, and many more.

Apply Early

Finance is about fueling innovation. We do this by hiring quality individuals with integrity ... computer science, data science, economics, or related quantitative field Creative and curious ...

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Computer Science Finance information

How is computer science used in finance?

Computer science in finance involves developing algorithms and software for trading, risk management, and data analysis. Professionals use programming languages like Python and tools such as machine learning models to optimize financial decision-making and automate processes.

What are the key skills and qualifications needed to thrive in Computer Science Finance, and why are they important?

To thrive in Computer Science Finance, you need strong analytical and programming skills, a solid understanding of financial concepts, and typically a degree in computer science, finance, or a related field. Familiarity with financial modeling tools, database management systems, and programming languages like Python, R, or SQL is highly valued, along with certifications such as CFA or FRM. Excellent problem-solving abilities, attention to detail, and effective communication are essential soft skills for collaborating with diverse teams and interpreting complex data. These skills are crucial for developing innovative financial solutions, ensuring data integrity, and driving informed decision-making in the fast-paced finance industry.

What is the difference between Computer Science Finance vs Data Analyst?

AspectComputer Science FinanceData Analyst
Required CredentialsBachelor's in Computer Science, Finance, or related fields; certifications like CFA or FRM beneficialBachelor's in Statistics, Economics, or related fields; certifications like CAP or Microsoft Data Analyst
Work EnvironmentFinancial institutions, tech firms, investment banks; often collaborative and fast-pacedCorporate offices, consulting firms, financial services; data-driven and analytical
Employer & Industry UsageFinance, banking, fintech, tech companiesFinance, marketing, healthcare, consulting

Computer Science Finance professionals combine technical skills with financial knowledge to develop algorithms, models, and software for financial analysis and trading. Data Analysts focus on interpreting data to inform business decisions across various industries. While both roles require analytical skills, Computer Science Finance emphasizes programming and financial expertise, whereas Data Analysts concentrate on data interpretation and reporting.

What is computer science finance?

Computer science finance is an interdisciplinary field that combines principles of computer science with finance. Professionals in this area use technology and programming to analyze financial data, develop trading algorithms, manage risk, and optimize investment strategies. Careers in computer science finance often involve roles such as quantitative analyst, financial software developer, or data scientist for investment firms, banks, or fintech companies. This field requires skills in programming (often Python, R, or C++), data analysis, and a solid understanding of financial markets and instruments.

Is finance and computer science a good combo?

Computer Science Finance combines technical programming skills with financial knowledge, making it valuable in areas like quantitative analysis, algorithmic trading, and financial modeling. Professionals in this field often use tools like Python, R, and SQL, and benefit from certifications such as CFA or FRM to enhance career prospects.

Can you get a finance job with a computer science degree?

A computer science degree can qualify you for finance jobs such as quantitative analyst, financial software developer, or data analyst, especially if you have skills in programming, data analysis, and financial modeling. Many finance roles value technical expertise, coding skills, and knowledge of financial tools like Excel, SQL, or Python. Additional certifications like CFA or FRM can enhance prospects in finance positions requiring specialized financial knowledge.

Is computer science dead due to AI?

Computer science remains a vital field for roles such as software developers, data scientists, and AI specialists. AI advances create new opportunities for innovation, requiring skills in programming, algorithms, and machine learning tools, ensuring continued demand for computer science expertise.

How does a professional in Computer Science Finance typically collaborate with both technical and financial teams?

Professionals in Computer Science Finance often serve as a bridge between technology and finance departments, translating financial requirements into technical solutions. They might collaborate closely with software engineers to develop financial models or automation tools, and work with analysts or traders to understand market needs and ensure technical solutions align with business goals. Effective communication is key, as they regularly participate in cross-functional meetings, manage project timelines, and provide updates to both technical and non-technical stakeholders. This role requires adaptability and the ability to explain complex concepts in accessible terms.

What Are Finance Jobs for Computer Science Majors?

Finance jobs for computer science majors focus on the analysis of financial data, the development of finance technology (fintech) software and applications to analyze financial markets and automate equities trading, and the creation of algorithms for analysis, fraud detection, and risk management. As a data scientist or quantitative analyst, you perform your duties for an investment firm or bank. If you are a risk management analyst, you work for financial institutions or life insurance companies. A computer science major can also develop software and configure databases for finance businesses or have cybersecurity responsibilities that include protecting data and systems from hackers.

What are popular job titles related to Computer Science Finance jobs in California? For Computer Science Finance jobs in California, the most frequently searched job titles are:
What job categories do people searching Computer Science Finance jobs in California look for? The top searched job categories for Computer Science Finance jobs in California are:
What cities in California are hiring for Computer Science Finance jobs? Cities in California with the most Computer Science Finance job openings:
Infographic showing various Computer Science Finance job openings in California as of June 2026, with employment types broken down into 94% Full Time, 4% Part Time, 1% Temporary, and 1% Contract. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution.
Data Scientist, Finance Forecasting

Data Scientist, Finance Forecasting

ClickHouse

San Francisco, CA • On-site

Other

Posted 19 days ago


Job description

ClickHouse is the fastest open-source analytical database in the world, processing billions of rows per second for thousands of organizations. As we scale our cloud business, the decisions that shape pricing, capacity planning, and go-to-market strategy need to be grounded in rigorous quantitative modeling, and that capability is being built from the ground up.

We're hiring a founding Data Scientist to build ClickHouse's Finance forecasting and measurement capability from the ground up. You'll own and build the forecasting models, causal measurement programs, and analytical frameworks that directly shape how leadership plans the business. You'll define the approach, build the infrastructure, and set the standard for how data science operates here.

Hybrid: We intend to fill this role in the San Francisco Bay Area, and expect this position to go into one of our Bay Area offices, Menlo Park and San Francisco, 1-2x per week. 

What You'll Be Doing:
  • Own and build production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration
  • Build forecasting systems that account for the dynamics of usage-based pricing, consumption patterns, and customer lifecycle across our cloud platform
  • Design and implement causal measurement frameworks to quantify the revenue impact of product launches, pricing changes, and GTM motions
  • Establish backtesting discipline and accuracy tracking as standing Finance metrics, making forecast quality visible and continuously improving
  • Contribute to shared analytics infrastructure and internal tooling that accelerates data science workflows across the organization
  • Translate model outputs into clear, actionable recommendations for Finance, Sales, and executive leadership
  • Partner with Data Engineering, Revenue Operations, and Product to build the feature pipelines and data foundations your models depend on
What You Bring Along:
  • Has an advanced degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Physics, Economics) or equivalent depth through production experience
  • Hands-on experience building and deploying ML and statistical systems, with meaningful time spent on forecasting or causal inference in production
  • Has deep applied statistics foundations, including comfort with time-series methods, state-space models, hierarchical approaches, or causal inference techniques
  • Is highly proficient in Python and SQL, with experience productionizing models in cloud-scale data environments
  • Has worked with modern analytical platforms such as ClickHouse, Snowflake, BigQuery, or Spark
  • Has experience forecasting consumption-based or usage-billed businesses (cloud, API, marketplace)
  • Has a bias toward action in ambiguous, early-stage environments and is comfortable defining the problem, not just solving it
  • Communicates clearly with executive stakeholders and can translate complex modeling work into actionable business recommendations
  • Is fluent with AI tools and workflows, including LLMs and AI coding assistants, and applies them effectively in analytical work
  • Is comfortable taking ownership of open-ended problems and building new functions from scratch