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Computer Science Jobs in Raleigh, NC (NOW HIRING)

Bachelor's degree in Analytics, Computer Science, Data Science, Operations Research, Economics, or a closely related field (or foreign education equivalent) and six (6) years of experience as a ...

D. in Applied Mathematics, Computer Science, Electrical Engineering, or a related technical discipline * 0-5 years of post-doctoral or equivalent research experience * Proficiency in scientific ...

D. in Applied Mathematics, Computer Science, Electrical Engineering, or a related technical discipline * 0-5 years of post-doctoral or equivalent research experience * Proficiency in scientific ...

Software Engineer II

Durham, NC · On-site

$45 - $48/hr

Bachelor's in Computer Science, Computer Engineering, Electrical or Electronic Engineering, or a related field; Master's degree preferred. A successful candidate in this position will possess strong ...

Software Engineer II

Durham, NC · On-site

$45 - $48/hr

Bachelor's in Computer Science, Computer Engineering, Electrical or Electronic Engineering, or a related field; Master's degree preferred. A successful candidate in this position will possess strong ...

Ability to explain computational thinking, abstraction, iteration, recursion, and software development life cycle while preparing students for computer science coursework and software engineering ...

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Computer Science information

See Raleigh, NC salary details

$54.9K

$80.8K

$95.3K

How much do computer science jobs pay per year?

As of Jul 9, 2026, the average yearly pay for computer science in Raleigh, NC is $80,788.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,300.00 and $90,900.00 per year, depending on experience, location, and employer.

What is the difference between Computer Science vs Software Developer?

AspectComputer ScienceSoftware Developer
Required CredentialsBachelor's or higher in CS or related fieldBachelor's in CS, Software Engineering, or related field often preferred
Work EnvironmentResearch labs, academia, tech companies, startupsTech companies, software firms, freelance projects
Industry UsageAcademic research, algorithm development, theoretical workBuilding, coding, testing software applications
Common Search/ComparisonFocuses on theoretical foundations and algorithmsFocuses on practical software creation and deployment

Computer Science and Software Developer roles often overlap, but Computer Science emphasizes theoretical foundations, algorithms, and research, while Software Developers focus on designing, coding, and maintaining software applications. Both roles require programming skills, but their primary focus and work environments differ.

What is computer science?

Computer science is the study of computers, computational systems, and how they process information. It covers a wide range of topics, including programming, algorithms, data structures, artificial intelligence, and software engineering. Computer scientists design and analyze software and hardware to solve problems and improve technology. The field is essential in many industries, from finance and healthcare to entertainment and research.

What Are Computer Science Jobs?

The computer science field provides a wide range of opportunities for technically talented individuals. Depending on your skills and interests, you can find computer science jobs as a software developer, hardware engineer, database administrator, computer systems analyst, network architect, information security analyst, or web developer. You need an analytical mind and strong technical skills to perform your job duties, which may be to develop, maintain, and troubleshoot computer systems, applications, or networks. Your responsibilities in a computer science job are often directly related to the business goals and outcomes of your employer.

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

To thrive in a Computer Science role, you need strong programming skills, problem-solving abilities, and a degree in computer science or a related field. Familiarity with languages like Python, Java, C++, version control systems such as Git, and software development methodologies is often required. Analytical thinking, attention to detail, and effective teamwork are valuable soft skills that set candidates apart. These skills ensure you can design efficient solutions, collaborate on complex projects, and adapt to rapidly evolving technologies.

What are some common challenges computer science professionals face when working on collaborative software projects?

Computer science professionals often encounter challenges such as coordinating with team members across different disciplines, managing version control in shared codebases, and ensuring clear communication of technical concepts to non-technical stakeholders. Navigating conflicting priorities and integrating diverse components can also be demanding, especially in agile environments with tight deadlines. Strong collaboration skills, openness to feedback, and familiarity with team tools like Git and project management platforms can help address these challenges effectively.
What are the most commonly searched types of Computer Science jobs in Raleigh, NC? The most popular types of Computer Science jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Computer Science jobs? Cities near Raleigh, NC with the most Computer Science job openings:
Infographic showing various Computer Science job openings in Raleigh, NC as of July 2026, with employment types broken down into 82% Full Time, 12% Part Time, and 6% Contract. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $80,788 per year, or $38.8 per hour.
Director, Data Science

Director, Data Science

Fidelity Investments

Durham, NC • On-site

Full-time

Retirement

Posted 4 hours ago


Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 266 frontline employees who took The Breakroom Quiz

16th of 146 rated financial services


Job description


Position Description:
Leads and oversees end-to-end data science initiatives, guiding teams through data cleansing, preparation, annotation, feature engineering, exploratory analysis, and model development. Provides strategic direction on Machine Learning (ML) pipeline architecture, ensures alignment with business objectives, and drives cross-functional collaboration to deliver scalable, high-impact solutions. Draws on in-depth knowledge of the business or function to provide business unit-wide solutions by building, testing and monitoring AI models. Researches and recommends new technologies, and seizes opportunities by staying abreast of publications, tools, and techniques from the global Artificial Intelligence (AI/ML) community, in support of the strategic direction of the business unit and to achieve business-unit-wide solutions.
Primary Responsibilities:
  • Identifies business opportunities and evaluates best approaches for predictive or prescriptive analytics.
  • Implements best practices for model development, iteration, as well as code management and conducts code reviews.
  • Draws key business insights from advanced quantitative analyses and presents findings to broader audience.
  • Leads the design and deployment of advanced analytics solutions that convert raw data into actionable intelligence.
  • Delivers scalable insights, while aligning analytics infrastructure with business priorities.
  • Directs the development and integration of analytics frameworks that transform raw data into strategic insights.
  • Ensures solutions are scalable, business-aligned, and drive data-informed decision-making across the organization.
  • Leads and oversees the full AI/ML lifecycle -- data ingestion, model development, training, deployment, and monitoring.
  • Identifies and consults with internal and external technical resources to produce cross-company strategic designs.
  • Consults on deployment of major project deliverables.
  • Initiates and drives project or strategy discussions with users or external groups to resolve issues.
  • Sets vision, goals, and direction of team/organization.
  • Plans and leads organization-wide initiatives.
  • Provides leadership, technical supervision, and expertise to multiple teams in broad technical areas on complex organization-wide projects.
  • Advises senior management on technical strategy.
  • Regularly provides guidance, training, and coaching to other team members for performance and career development.
  • Identifies and plans for future resource needs.

Education and Experience:
Bachelor's degree in Analytics, Computer Science, Data Science, Operations Research, Economics, or a closely related field (or foreign education equivalent) and six (6) years of experience as a Director, Data Science (or closely related occupation) designing and building complex and scalable Artificial Intelligence (AI) pipelines to improve customer experience and drive business results in the financial services industry.
Or, alternatively, Master's degree in Analytics, Computer Science, Data Science, Operations Research, Economics, or a closely related field (or foreign education equivalent) and four (4) years of experience as a Director, Data Science (or closely related occupation) designing and building complex and scalable Artificial Intelligence (AI) pipelines to improve customer experience and drive business results in the financial services industry.
Skills and Knowledge:
Candidate must also possess:
  • Demonstrated Expertise ("DE") developing supervised and unsupervised Machine Learning (ML) algorithms -- regression, gradient boosting trees/random forest, neural network, feature selection/reduction, clustering, and parameter tuning -- using R, Python, and SAS programming languages; and analyzing and evaluating model results by creating data visualizations and business intelligence reports in Tableau and Adobe Analytics.

  • DE performing data wrangling and feature engineering for large, complex data across Cloud and on-premise data warehouses -- Oracle, Greenplum/Postgres, Hadoop/Hive, Snowflake, S3, and Redis -- using SQL, Python, and database specific SQL; standardizing and optimizing complex queries using database techniques -- partitioning and parallel processing; aggregating time series and transaction tables; creating appropriate features for modeling out of structured and unstructured data; detecting and preventing data leakage and model biases through model fairness measures using open-source AI fairness and ethics libraries.

  • DE analyzing technology solutions for supporting model deployment and integration in Cloud and on premise environments; and building model deployment and integration workflows on Amazon Web Services (AWS), on-premise Hadoop, and UNIX platforms through Git, Jenkins, Python scripts, cron jobs, step functions, Docker images, and APIs.

  • DE migrating existing AI/ML processes from on-premise environments to AWS platforms, using Extract- Transform-Load (ETL) procedures, Python, and Docker containers; creating data quality guardrails to validate model inputs and outputs using ICEDQ; and addressing financial services Cloud security constraints and record systems for workplace services -- 401(K), defined benefits, and workplace compensation and retirement plans, using AWS security tools.

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Certifications:
Category:
Data Analytics and Insights
Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

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