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Computer Science Economics Jobs in North Carolina

Bachelor's degree in data science, statistics, computer science, economics, operations research, engineering, or related quantitative field * Minimum 3 years of experience applying data science ...

Bachelor's degree in data science, statistics, computer science, economics, operations research, engineering, or related quantitative field * Minimum 3 years of experience applying data science ...

Bachelor's degree in data science, statistics, computer science, economics, operations research, engineering, or related quantitative field * Minimum 3 years of experience applying data science ...

Bachelor's degree in data science, statistics, computer science, economics, operations research, engineering, or related quantitative field * Minimum 3 years of experience applying data science ...

Bachelor's Degreein Statistics, Mathematics, Computer Science, Data Science, Economics, or related quantitative field required. Work Experience: * 2-4 years applied data science, quantitative ...

Bachelor's Degreein Statistics, Mathematics, Computer Science, Data Science, Economics, or related quantitative field required. Work Experience: * 2-4 years applied data science, quantitative ...

Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in ...

Showing results 21-40

Computer Science Economics information

See North Carolina salary details

$10K

$89.1K

$145.9K

How much do computer science economics jobs pay per year?

As of Aug 20, 2026, the average yearly pay for computer science economics in North Carolina is $89,062.00, according to ZipRecruiter salary data. Most workers in this role earn between $20,000.00 and $145,400.00 per year, depending on experience, location, and employer.

What is a computer science economics?

A Computer Science Economics job combines computing, data analysis, and economic principles to solve complex business and financial problems. Professionals in this field work with algorithms, machine learning, and economic models to analyze trends, optimize decision-making, and improve efficiency. They may work in industries like finance, tech, or policy analysis, using data-driven methods to drive insights and innovation.

What does a computer science economics do?

Professionals in Computer Science Economics roles blend data analysis, economic modeling, and software development to provide insights that guide business strategies and policy decisions. On a typical day, you might analyze large datasets, build predictive economic models, collaborate with data engineers or economists, and present findings to stakeholders. Many roles are highly collaborative, often involving teamwork with both technical and non-technical colleagues to solve complex, real-world business or economic problems. The work environment can range from consulting firms to financial institutions or tech companies, offering a dynamic and intellectually stimulating setting with opportunities for continued learning and career growth.

What skills and qualifications are needed for a computer science economics?

To excel in a Computer Science Economics role, candidates typically need a strong background in both computer science fundamentals (such as programming, algorithms, and data structures) and economic theory, often evidenced by degrees in these or related fields. Familiarity with analytical tools like Python, R, SQL, and statistical modeling software, as well as experience with data visualization platforms, are commonly required. Strong communication, critical thinking, and problem-solving abilities enable effective collaboration across multidisciplinary teams. These skills and qualifications are crucial for leveraging computational techniques to analyze complex economic data and deliver actionable insights in technology-driven industries.

Is computer science and economics a good combination?

Computer Science Economics combines technical programming skills with economic analysis, making it valuable for roles in data analysis, financial modeling, and technology-driven economic research. Professionals in this field often use programming languages like Python or R and may pursue certifications in data science or economics to enhance their expertise.

What are the top 3 highest paying jobs in computer science?

In computer science, the highest paying roles typically include software engineering managers, data scientists, and solutions architects. These positions often require advanced technical skills, experience, and sometimes certifications, and they tend to offer salaries significantly above the industry average.

What can you do with a computer science and economics degree?

A computer science and economics degree prepares individuals for roles such as data analyst, financial analyst, software developer, or economic consultant. These roles often require skills in programming, data analysis, and understanding economic principles, and may involve working with tools like Python, R, or SQL in various industries including finance, technology, and consulting.

What are popular job titles related to Computer Science Economics jobs in North Carolina?

For Computer Science Economics jobs in North Carolina, the most frequently searched job titles are:

What job categories do people searching Computer Science Economics jobs in North Carolina look for?

The top searched job categories for Computer Science Economics jobs in North Carolina are:

Infographic showing various Computer Science Economics job openings in North Carolina as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 10% Part Time, 7% Temporary, 2% Contract, and 1% Nights. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution, with an average salary of $89,062 per year, or $42.8 per hour.

Senior AI Scientist - Credit Karma (Partner Decision Science)

Intuit

Charlotte, NC • On-site

Full-time

Re-posted 20 days ago


Intuit rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

107th of 245 rated software companies


Job description

Credit Karma is looking for a Senior AI Scientist to join our Partner Decision Science team - the group at the center of how the country's largest banks and fintech lenders build, target, and approve on the Credit Karma Lightbox platform. In this role, you will be the technical bridge between Credit Karma's decision-science platform and the data science and credit-risk teams at our partners, turning their objectives into production models that increase conversion and revenue while giving our members greater certainty that they'll be approved for the products they're matched with.

This is a highly cross-functional role. You will partner closely with internal business development, engineering, product, and data and analytics teams, as well as with external partner teams that range from hands-on analysts to senior leaders. Success depends as much on your ability to influence and translate across these audiences as it does on your technical depth - we are looking for a scientist who can go deep in the data and models, then clearly explain the 'so what' to a room of business and partner stakeholders.

You will pair strong machine learning skills with real business acumen, applying techniques that span credit-risk and targeting modeling, recommendation and ranking, experimentation, and - where it adds value - generative AI, all in service of the most relevant, best-timed financial recommendations for our members.


Responsibilities

  • Serve as the technical bridge between Credit Karma's decision-science platform and the data science and credit-risk teams at partner banks and fintech lenders, ensuring partner data and modeling requirements are met end to end.

  • Design, build, and optimize large-scale targeting and approval models that grow conversion and revenue for Credit Karma and its partners while improving approval certainty for members.

  • Advance the partner modeling toolkit - feature engineering on consumer credit and bureau data, modern ML methods, and emerging GenAI applications - to lift partner model performance and member relevance.

  • Build strong relationships with partner data science and risk teams, from individual contributors to managers and directors, and coach them on the capabilities of the Credit Karma platform.

  • Partner cross-functionally with internal business development, engineering, product, and data and analytics teams to translate partner needs into platform capabilities and move models into production.

  • Represent the Partner Decision Science team in cross-functional and partner-facing meetings, translating complex technical subject matter for executive and non-technical audiences and advocating for partners inside Credit Karma and for Credit Karma with partners.

  • Act like an owner: identify high-impact opportunities across the partner portfolio, propose solutions, and see them through to production and measurable results.


Qualifications

  • MS in Statistics, Mathematics, Computer Science, Economics, Physics, or a related quantitative discipline (or a BS with equivalent applied experience).

  • Approximately 5+ years in credit-risk analytics, data science, or risk management - at a bank, fintech, or credit bureau - with work spanning credit underwriting, model development, or customer valuation.

  • Deep, hands-on understanding of credit data, including bureau attributes, risk scores, and alternative data sources.

  • Expert proficiency in Python and SQL, with experience in modern ML frameworks and comfort operating on large-scale data (e.g., BigQuery or a comparable warehouse).

  • Proven ability to explain complex modeling concepts to non-technical and executive stakeholders and to connect model performance to business outcomes.

  • Exceptional verbal and written communication skills, with the ability to convey complex ideas and influence senior audiences in their decision-making.

  • External partner-facing experience is a plus.


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Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: 



Employment Type: Full-Time

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