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Data Science Intern Jobs in Raleigh, NC (NOW HIRING)

Fidelity Investments

Director, Data Science

Durham, NC · On-site

Leads and oversees end-to-end data science initiatives, guiding teams through data cleansing, preparation, annotation, feature engineering, exploratory analysis, and model development. Provides ...

Fidelity Investments

Director, Data Science

Durham, NC · On-site

Leads and oversees end-to-end data science initiatives, guiding teams through data cleansing, preparation, annotation, feature engineering, exploratory analysis, and model development. Provides ...

Duke University

NONDUKE STUDENT/INTERN

Durham, NC

Strong interest in community engagement, data science, or social impact * Experience with data ... Intern | Program Planner Intern | Community Impact Intern What You'll Do: Responsibilities will ...

Duke University

NONDUKE STUDENT/INTERN

Durham, NC · On-site

Strong interest in community engagement, data science, or social impact * Experience with data ... Intern | Program Planner Intern | Community Impact Intern What You'll Do: Responsibilities will ...

ABB

AI & Data Scientist Intern - Fall 2026

Cary, NC · Hybrid

$20 - $34/hr

Currently enrolled in a bachelor's or master's degree program in computer science, data science, or related fields, in the United States. * Intern must have reliable transportation to and from the ...

Cigna

Data Science Director - Remote

Raleigh, NC · On-site +1

As the Data Science Director for Pricing & Underwriting, you will lead high-impact teams that build and evolve machine learning models influencing business growth, risk selection, forecasting ...

New

Labcorp

Associate Data Scientist

Durham, NC · Hybrid

$57K - $57K/yr

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics ... Employees regularly scheduled to work less than 20 hours, Casual, Intern, and Temporary employees ...

Advance Auto Parts, Inc.

Data Scientist

Raleigh, NC · On-site

Work closely with stakeholders to understand business challenges and translate them into data science solutions and work in the end-to-end solutioning. Collaborate with cross-functional teams to ...

Advance Auto Parts

Data Scientist

Raleigh, NC · On-site +1

Work closely with stakeholders to understand business challenges and translate them into data science solutions and work in the end-to-end solutioning. Collaborate with cross-functional teams to ...

Redhat

Principal Data Scientist

Raleigh, NC · On-site +1

$147K - $243K/yr

S. Build data science solutions for business challenges including customer propensity, product forecasting, and recommender systems. Use machine learning, data mining, and statistical methods to ...

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How much do data science intern jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for data science intern in Raleigh, NC is $21.88, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $23.85 per hour, depending on experience, location, and employer.

What types of projects can I expect to work on as a Data Science Intern, and how will I collaborate with other team members?

As a Data Science Intern, you can expect to work on a variety of projects such as data cleaning, exploratory data analysis, building predictive models, or assisting with data visualization tasks. You'll often collaborate closely with data scientists, engineers, and sometimes business analysts, participating in team meetings and brainstorming sessions. Interns are usually given clearly defined tasks that contribute to larger projects, allowing you to learn from experienced professionals while making a meaningful impact. Regular check-ins and mentorship are typical, providing you with feedback and professional growth opportunities throughout your internship.

What does a Data Science Intern do?

A Data Science Intern typically assists with collecting, cleaning, and analyzing data to support business decisions or research. They work under the supervision of experienced data scientists, helping to build and test predictive models, create data visualizations, and present findings. Interns often use programming languages such as Python or R, and tools like SQL, to manipulate data. The role is designed to provide hands-on experience with real-world data science projects and help interns develop technical and analytical skills.

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

To thrive as a Data Science Intern, you need a solid grasp of statistics, data analysis, and programming (often in Python or R), typically supported by coursework in computer science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau), machine learning libraries (such as scikit-learn or TensorFlow), and version control systems (like Git) is commonly expected. Strong problem-solving abilities, communication skills, and a willingness to learn help interns collaborate effectively and translate data insights for diverse audiences. These skills and qualities ensure that interns can contribute meaningfully to projects, adapt quickly, and bridge the gap between raw data and actionable business solutions.
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Data Science Intern jobs near you
Director, Data Science

Director, Data Science

Fidelity Investments

Durham, NC • On-site

Full-time

Retirement

Re-posted 3 days ago

Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 266 frontline employees who took The Breakroom Quiz

17th of 148 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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