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

This role sits at the intersection of AI, analytics, data science, and business strategy-transforming complex data into actionable insights, predictive solutions, and measurable outcomes. The ideal ...

Senior Data Analyst

Raleigh, NC · On-site

$110/hr

This role sits at the intersection of AI, analytics, data science, and business strategy-transforming complex data into actionable insights, predictive solutions, and measurable outcomes. The ideal ...

Senior Data Analyst

Raleigh, NC · On-site

$110/hr

This role sits at the intersection of AI, analytics, data science, and business strategy-transforming complex data into actionable insights, predictive solutions, and measurable outcomes. The ideal ...

Data Analyst

Raleigh, NC · On-site

$72K - $80K/yr

Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field. * 3+ years of experience in data analysis, with proficiency in Microsoft tools and Power BI. * Strong analytical ...

Data Analyst

Raleigh, NC · On-site

$72K - $80K/yr

Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field. * 3+ years of experience in data analysis, with proficiency in Microsoft tools and Power BI. * Strong analytical ...

Data Science Tutor

Durham, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Data Science Tutor

Chapel Hill, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Data Science Tutor

Raleigh, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

LexisNexis is a global provider of information-based analytics and decision tools for professional and business customers. The Manager, Data Science will lead the development of advanced AI and ...

Data Analyst

Raleigh, NC · On-site

$30 - $35/hr

Bachelor's degree in Data Analytics, Computer Science, Information Systems, Statistics, Public Health, Business Analytics, or a related field preferred. * Equivalent combination of education and ...

... creation, data analysis and visualization, and collaboration. Three branch libraries focus on ... The Data Science Services (DSS) department (6 librarians, 1 library specialist, plus graduate ...

Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences * Proficiency in Python, including ...

MANAGER, DATA SCIENCE The Manager of Data Science will build and lead a focused, high-impact team ... Operating in close partnership with business units, Central Analytics, and Data Engineering, this ...

Bachelor's degree in physical sciences, mathematical sciences, or a related STEM field. * 2+ years of experience in analyzing data strongly preferred. * LC-MS experience a plus. * Strong analytical ...

Bachelor's degree in physical sciences, mathematical sciences, or a related STEM field. * 2+ years of experience in analyzing data strongly preferred. * LC-MS experience a plus. * Strong analytical ...

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Showing results 1-20

Data Analyst Data Science information

See Raleigh, NC salary details

$33.1K

$80.3K

$132.2K

How much do data analyst data science jobs pay per year?

As of Jun 26, 2026, the average yearly pay for data analyst data science in Raleigh, NC is $80,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,800.00 and $94,300.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

Data analysts and data scientists can start their careers at any age, including 40 or older. Success in data science depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, which can be learned at any stage of life. Many professionals transition into data roles later in their careers with dedication and continuous learning.

How do Data Analysts in Data Science typically collaborate with other departments or teams?

Data Analysts in Data Science frequently work cross-functionally, partnering with teams such as engineering, product management, marketing, and business intelligence. They translate complex data findings into actionable insights and tailor their communication to both technical and non-technical stakeholders. Regular collaboration may involve participating in meetings to understand business needs, designing dashboards for different teams, and providing data-driven recommendations to support company objectives. This collaborative environment not only enhances project outcomes but also fosters continuous learning and professional growth.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data analysts often use this concept to focus on the most impactful variables or features during analysis and modeling to improve efficiency and accuracy.

What does a Data Analyst in Data Science do?

A Data Analyst in Data Science collects, processes, and analyzes large sets of data to help organizations make informed decisions. They use statistical techniques and data visualization tools to identify trends, patterns, and insights from data. Their responsibilities often include cleaning data, creating reports, and communicating findings to stakeholders. Data Analysts play a key role in helping businesses optimize operations, understand customer behavior, and solve complex problems using data-driven approaches.

Can data science work as a data analyst?

Data science and data analysis are related fields, but they have different focuses. Data scientists often develop models and algorithms using programming languages like Python or R, while data analysts primarily interpret data, generate reports, and use tools like Excel or SQL. Skills in statistical analysis, data visualization, and understanding business needs are essential for both roles, and some professionals transition between them based on experience and training.

What is the difference between Data Analyst Data Science vs Data Engineer?

AspectData Analyst Data ScienceData Engineer
Required SkillsStatistics, programming (Python, R), data visualizationDatabase systems, ETL pipelines, programming (Python, Java)
Work EnvironmentAnalyzing data, building models, reportingBuilding and maintaining data infrastructure
CertificationsData Science certifications, SQL, PythonCloud certifications, database management
Industry UsageBusiness analysis, predictive modelingData infrastructure, big data systems

Data Analyst Data Science focuses on analyzing data and creating models to inform decisions, while Data Engineers build the systems that collect, store, and process data. Both roles require programming skills and often overlap in tools like Python and SQL, but their core responsibilities differ significantly.

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

To thrive as a Data Analyst in Data Science, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Familiarity with tools like SQL, Python or R, and data visualization platforms such as Tableau or Power BI, along with industry-recognized certifications, is highly valued. Attention to detail, problem-solving abilities, and effective communication skills help you interpret data insights and convey findings to stakeholders. These skills are crucial for transforming raw data into actionable intelligence that drives strategic business decisions.

Is AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can augment their work, human expertise remains essential for interpreting results, understanding context, and communicating findings effectively. Data analysts who develop skills in machine learning, programming, and data visualization will continue to be valuable in the evolving data science environment.
What are popular job titles related to Data Analyst Data Science jobs in Raleigh, NC? For Data Analyst Data Science jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Data Analyst Data Science jobs in Raleigh, NC look for? The top searched job categories for Data Analyst Data Science jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Data Analyst Data Science jobs? Cities near Raleigh, NC with the most Data Analyst Data Science job openings:

$110/hr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 18 days ago


Job description

Reports To: Chief of Staff

 

This role requires a full-time onsite presence in Durham, NC

 

Target Base Range: $110 - 120k (Final compensation commensurate with experience and qualifications) 

 

Please note: We are only able to consider candidates who are U.S. citizens or lawful permanent residents (green card holders) and who do not require current or future visa sponsorship of any sort.

 

About the Role

We are seeking a highly skilled Senior Data Analyst with a strong foundation in data science, statistical modeling, and advanced analytics and AI platforms to drive data-informed decision-making across the organization. This role sits at the intersection of AI, analytics, data science, and business strategy-transforming complex data into actionable insights, predictive solutions, and measurable outcomes.

The ideal candidate is comfortable working with large, complex datasets, building advanced analytical models, and communicating findings clearly to both technical and non-technical stakeholders.

Key Responsibilities

Data Analytics & Insights

  • Analyze large, complex, and multi-source datasets to uncover trends, patterns, and actionable insights.
  • Translate analytical findings into clear recommendations that influence product strategy, operations, and executive decision-making.
  • Develop data-driven forecasts, simulations, and scenario analyses to support strategic planning.
  • Apply statistical techniques (e.g., regression, hypothesis testing, time-series analysis, clustering) to solve complex business problems.

Data Engineering & Tooling (Analytics-Focused)

  • Develop AI models and datasets to inform business decisions, correlate data and drive decision-making.
  • Write efficient, well-documented SQL and/or Python/R code for data extraction, transformation, and analysis.
  • Partner with data engineering teams to ensure high-quality, well-structured, and reliable datasets.
  • Maintain internal utilization models and support continual enhancement and development of utilization models.

Leadership & Collaboration

  • Act as a thought leader and mentor for team members and business partners.
  • Collaborate closely with stakeholders across product, finance, operations, marketing, and quality.
  • Help define best practices for analytics, experimentation, and data science across the organization.

Required Qualifications

  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field (Master's degree preferred).
  • A minimum of 5 years of experience in data analytics, data science, or a related analytical role.
  • Strong knowledge of statistical analysis, modeling techniques, and data science methodologies.
  • Experience working with large datasets and modern data platforms (e.g., cloud data warehouses, distributed systems).
  • Proven ability to translate data insights into business impact.
  • Excellent communication and stakeholder management skills.

Preferred / Nice-to-Have Qualifications

  • Experience deploying or operationalizing machine learning models in a production environment.
  • Familiarity with A/B testing frameworks and experimental design.
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and modern analytics stacks.
  • Knowledge of data governance, data quality, and privacy best practices.
  • Prior experience in EV Charging, consumer behavior, technical quality analytics.

What Success Looks Like in This Role

  • You own the pursuit of the truth in everything you do.
  • Analytical insights consistently influence strategic and operational decisions with clarity and conviction.
  • Predictive models and advanced analyses improve forecasting accuracy and business outcomes.
  • Stakeholders trust and rely on analytics outputs for critical decisions.
  • Analytics processes are scalable, efficient, and reproducible.

IONNA is committed to fair and equitable compensation practices through a competitive base salary, as well as offering bonus programs, comprehensive benefits such as medical, dental, vision, life, 401(K), and paid holidays. Actual base salaries are based on several factors unique to each candidate, including but not limited to skill set, experience, certifications, and specific work location.

We are committed to an inclusive and diverse team. IONNA is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.