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Internship Azure Data Scientist Jobs in Raleigh, NC

Pwc

Data Engineer - Senior Associate

Raleigh, NC · On-site

$77K - $202K/yr

... and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering ... Architect, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer ...

Clarkston Consulting

Data Architect

Raleigh, NC · On-site +1

$62 - $79.75/hr

... sciences, consumer products, and retail industries. Together, we can find the answers to our ... Design, prototype, and develop Big Data Platforms utilizing Azure or AWS * Translate business goals ...

Hearst

Senior Azure Cloud Engineer (.NET + AI Tools)

Durham, NC · On-site

$101K - $138K/yr

Troubleshoot complex issues across APIs, microservices, data pipelines, and Azure-managed services ... Bachelor's degree in Computer Science, Software Engineering, or a related technical field. * 5-8+ ...

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All JobsAzure Data Scientist JobsInternship Azure Data Scientist JobsInternship Azure Data Scientist Jobs in Raleigh, NC

Internship Azure Data Scientist information

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$44.7K

$160.4K

$236.7K

How much do internship azure data scientist jobs pay per year?

As of Aug 22, 2026, the average yearly pay for internship azure data scientist in Raleigh, NC is $160,411.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,800.00 and $165,300.00 per year, depending on experience, location, and employer.

What is an internship Azure Data Scientist?

An Internship Azure Data Scientist is an entry-level or student role that involves working with data science tools and techniques on Microsoft Azure's cloud platform. Interns in this position typically assist with data analysis, machine learning model development, and data pipeline creation using Azure services such as Azure Machine Learning, Data Factory, and Databricks. The internship provides hands-on experience with cloud-based data science workflows and helps interns build practical skills for a career in data science. Responsibilities may include cleaning and preparing data, training models, and visualizing results to support business decisions. This role is ideal for students or recent graduates interested in cloud computing and analytics.

What types of projects and responsibilities can I expect as an internship Azure Data Scientist?

As an Azure Data Scientist intern, you'll typically work on data-driven projects such as developing machine learning models, preparing and cleaning datasets, and performing exploratory data analysis using Microsoft Azure tools. You'll likely collaborate closely with data engineers, software developers, and senior data scientists to integrate solutions into cloud environments. Interns often participate in regular team meetings, present findings, and may contribute to optimizing existing data pipelines. This hands-on experience provides a strong foundation for a future career in cloud-based data science roles.

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

To thrive as an Internship Azure Data Scientist, you need foundational knowledge in statistics, data analysis, and programming languages such as Python or R, often supported by coursework or a degree in a STEM field. Familiarity with Microsoft Azure cloud services, data modeling tools, and machine learning frameworks is typically expected, and certifications like Microsoft Certified: Azure Data Scientist Associate can be beneficial. Strong problem-solving abilities, eagerness to learn, and effective communication skills help interns collaborate and convey technical findings clearly. These skills ensure interns can contribute meaningfully to data-driven projects while adapting quickly to the evolving demands of cloud-based analytics environments.

What is the difference between Internship Azure Data Scientist vs Data Analyst Intern?

AspectInternship Azure Data ScientistData Analyst Intern
Required SkillsAzure cloud services, basic data science, programming (Python, R), machine learning fundamentalsData visualization, SQL, Excel, basic statistical analysis
Work EnvironmentTech companies, cloud-focused teams, project-basedBusiness teams, reporting, data cleaning and analysis
CertificationsAzure Fundamentals, basic data science coursesNone typically required, basic Excel/SQL knowledge

Internship Azure Data Scientist roles focus on applying machine learning and cloud-based data science techniques using Azure services, often in tech or cloud-centric environments. Data Analyst Interns primarily handle data cleaning, visualization, and reporting tasks within business contexts. While both roles require foundational data skills, Azure Data Scientist internships emphasize cloud and machine learning expertise, whereas Data Analyst Internships focus on data interpretation and presentation.

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Internship Azure Data Scientist jobs near you

Data Lead / Architect with Life Science/ CRO

Precision Technologies Corp

Research Triangle Park, NC • On-site

Full-time

Re-posted 25 days ago

Job description

Role: Data Lead / Architect with Life Science/ CRO

Location: Research Triangle Park, NC 27709 (Hybrid)

Hire Type: Fulltime

Experience: 10+ years of experience

Must Have Skills Required:  Architect with familiarity with clinical systems (e.g., EDC, eTMF, CTMS, SAS, Argus) and data standards (e.g., CDISC, STDM).

Preferred Skills:  Experience with cloud-based data platforms like Azure data bricks and worked on Data Architecture. Knowledge of machine learning and data analytics.

Job Description:

The Lead, Data and Integrations will be responsible for creating and executing an enterprise-wide data strategy, encompassing all aspects of data management, including data mastering, data cleansing, data cataloging, and data architecture. This role will also oversee the development and operation of the enterprise data lake and standardize the integrations approach within the organization, transitioning from a complex mesh of point-to-point integrations to a hub-and-spoke model.

The ideal candidate will have a proven track record in forming teams, selecting and implementing technologies, and supporting the needs of a growing clinical research organization (CRO). Additionally, this role will be responsible for ensuring the security of enterprise data and compliance with data privacy and security standards. The role will also design data infrastructure to support AI and advanced analytics use cases.

 

Qualifications

  • Proven experience in building enterprise data lakes and integration platforms in a CRO or life sciences setting.
  • Familiarity with clinical systems (e.g., EDC, eTMF, CTMS, SAS, Argus) and data standards (e.g., CDISC, STDM).
  • Strong understanding of data privacy, compliance (21 CFR Part 11), and security protocols.
  • Experience leading cross-functional teams and vendor partnerships.
  • Excellent communication and leadership skills.

 

Key Responsibilities

1. Enterprise Data Strategy

  • Define and implement a comprehensive data governance framework.
  • Oversee data mastering, cleansing, cataloging, and architecture.
  • Lead the development and operation of an enterprise data lake (databricks).

2. Integration Modernization

  • Replace point-to-point integrations with a hub-and-spoke model.
  • Standardize integration protocols across clinical, operational, and corporate systems.
  • Collaborate with IT and business units to ensure scalable and secure data flows.

3. Data Security and Compliance

  • Implement and maintain robust data security measures to protect enterprise data.
  • Ensure compliance with data privacy regulations (e.g., GDPR, HIPAA) and security standards (e.g., ISO 27001).
  • Conduct regular security audits and risk assessments to identify and mitigate vulnerabilities.

4. AI and Advanced Analytics Infrastructure

  • Design and implement data infrastructure to support AI and advanced analytics use cases.
  • Collaborate with data scientists and analysts to ensure data availability and quality for machine learning models and analytics.
  • Integrate AI and machine learning capabilities into the data platform to drive insights and innovation.

5. Technology and Team Leadership

  • Select and implement modern data and integration platforms.
  • Build and lead a cross-functional team of data engineers, architects, and integration specialists.
  • Partner with stakeholders across Clinical, Corporate, and Commercial teams.

 

Preferred Qualifications

  • Experience with cloud-based data platforms and integration tools.
  • Knowledge of machine learning and data analytics.
  • Certification in data management or related fields