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Data Science 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 ...

Varsity Tutors

Data Science Tutor

Chapel Hill, NC · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Varsity Tutors

Data Science Tutor

Durham, NC · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Varsity Tutors

Data Science Tutor

Raleigh, NC · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

NCSU

Data Science Librarian

Raleigh, NC · On-site

The Data Science Services (DSS) department (6 librarians, 1 library specialist, plus graduate student assistants) helps students and other researchers develop critical data science and visualization ...

McGough

Manager, Data Science

Raleigh, NC · On-site

MANAGER, DATA SCIENCE The Manager of Data Science will build and lead a focused, high-impact team solving complex, high-value business problems through applied data science. This role defines how ...

McGough Construction

Manager, Data Science

Raleigh, NC · On-site

MANAGER, DATA SCIENCE The Manager of Data Science will build and lead a focused, high-impact team solving complex, high-value business problems through applied data science. This role defines how ...

LexisNexis

Manager Data Science

Raleigh, NC · On-site +1

$115K - $192K/yr

The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles ( About the Role As a Manager, Data ...

NCSU

Lecturer of Data Science

Raleigh, NC · On-site

$4.0K/wk

The Data Science and AI Academy's goal is to network and catalyze data science across all three pillars of the university's land-grant mission: education, research and service to the state of North ...

NCSU

Lecturer of Data Science

Raleigh, NC

$4.0K/wk

The Data Science and AI Academy's goal is to network and catalyze data science across all three pillars of the university's land-grant mission: education, research and service to the state of North ...

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 ...

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 ...

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All JobsData Science JobsData Science Jobs in Raleigh, NC

Data Science information

See Raleigh, NC salary details

$36.4K

$119.2K

$190.8K

How much do data science jobs pay per year?

As of Jul 19, 2026, the average yearly pay for data science in Raleigh, NC is $119,181.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,600.00 and $132,100.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Raleigh, NC? The most popular types of Data Science jobs in Raleigh, NC are:
What are popular job titles related to Data Science jobs in Raleigh, NC? For Data Science jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Raleigh, NC look for? The top searched job categories for Data Science jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Data Science jobs? Cities near Raleigh, NC with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Raleigh, NC as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $119,181 per year, or $57.3 per hour.
Director, Data Science

Director, Data Science

Fidelity Investments

Durham, NC • On-site

Full-time

Retirement

Posted 10 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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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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