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Full Time Data Analytics Intern Jobs (NOW HIRING)

Synchrony

BLP Intern - Data Analytics

Stamford, CT · On-site

... 1, the Intern Summer Series to meet and network with leaders around the business, and ongoing support from a team and mentors who are invested in your success. Data Analytics BLP Internship ...

Go! Retail Group

Financial Analytics Intern

Austin, TX · On-site

$17.50 - $23/hr

Job Type Full-time Description Who we are: Go! Retail Group is based in Austin, Texas, a national ... The successful candidate will have a strong desire to dive into current and historical data ...

ArcelorMittal

Data Analytics Co-Op

Detroit, MI

Check us out: www.amtbna.com We are looking for a Data Analytics Co-Op AMTB is seeking a motivated and detail-oriented Data Analytics Intern to join our team and contribute to the business ...

ArcelorMittal

Data Analytics Co-Op

Detroit, MI · On-site

Check us out: www.amtbna.com We are looking for a Data Analytics Co-Op AMTB is seeking a motivated and detail-oriented Data Analytics Intern to join our team and contribute to the business ...

ThyssenKrupp

Analytics

Middleburg Heights, OH · On-site

... with data visualization and Power Platform tools. The Analytics Intern reports to the V.P. of ... Currently enrolled full-time in an accredited university. Junior or Senior academic standing.

The GEO Group

DATA INTELLIGENCE INTERN

Boca Raton, FL · On-site

$20/hr

NO REMOTE OR HYBRID OPPORTUNITIES** Full-time employees will enjoy a competitive benefits package ... The Data Intelligence Intern will support the Division of Analytics, Intelligence, and Reporting by ...

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How much do full time data analytics intern jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for full time data analytics intern in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is the difference between Full Time Data Analytics Intern vs Data Analyst?

AspectFull Time Data Analytics InternData Analyst
QualificationsTypically pursuing or recently completed a bachelor's degree in data-related fieldsBachelor's degree or higher in data analysis, statistics, or related fields; sometimes requires experience
Work EnvironmentInternship programs within companies, often part-time or temporaryFull-time, permanent roles within organizations across industries
ResponsibilitiesAssisting with data collection, cleaning, and basic analysis under supervisionPerforming in-depth data analysis, creating reports, and providing insights independently

In summary, a Full Time Data Analytics Intern is an entry-level position aimed at gaining practical experience, often part of an internship program. A Data Analyst is a more experienced, full-time role responsible for comprehensive data analysis and decision support within organizations.

What cities are hiring for Full Time Data Analytics Intern jobs? Cities with the most Full Time Data Analytics Intern job openings:
What are the most commonly searched types of Data Analytics Intern jobs? The most popular types of Data Analytics Intern jobs are:
Full Time Data Analytics Intern jobs near you

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 9 days ago

Job description

Ph.D. Graduate Intern – Quantitative Portfolio Risk Analytics (Cross-Disciplinary)

Position Overview
We are seeking an exceptional Ph.D. graduate student to join our team as a Quantitative Portfolio Risk Analytics Intern. This role focuses on developing and applying advanced analytical methods to understand portfolio risk, market structure, and complex financial systems.
We are intentionally recruiting from cross-disciplinary, research-driven backgrounds. Doctoral candidates from fields such as physics, astrophysics, math, applied mathematics, statistics, engineering, economics, computer science, quantum computing, biotech, and other data-intensive sciences are strongly encouraged to apply—especially those interested in translating rigorous quantitative methods into real-world financial applications.
Key Responsibilities
  • Develop and enhance quantitative models for portfolio risk, including factor-based and statistical approaches 
  • Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of risk 
  • Design and implement analytical tools and pipelines using Python and SQL 
  • Contribute to model validation, backtesting, and performance evaluation 
  • Collaborate with risk, engineering, and data teams to improve model scalability and data infrastructure 
  • Communicate complex quantitative insights through clear visualizations and technical summaries 
  • Apply advanced methodologies from your discipline (e.g., stochastic modeling, optimization, machine learning, or geometric/topological approaches) to improve risk analytics 
Required Qualifications
  • Currently enrolled in a graduate Ph.D. program in a highly quantitative field (e.g., Math, Applied Mathematics, Physics, Astrophysics, Statistics, Computer Science, Engineering, Financial Engineering, Economics, Biotech or other data-driven disciplines) 
  • Strong foundation in probability, statistics, and numerical methods 
  • Proficiency in Python (NumPy, pandas, or similar) and/or SQL 
  • Experience working with large datasets and implementing quantitative models 
  • Ability to think rigorously about complex systems and translate theory into practical solutions 
Preferred Qualifications
  • Familiarity with quantitative finance concepts (e.g., portfolio theory, factor models, volatility modeling, Value-at-Risk) 
  • Experience with scientific computing, optimization, or machine learning 
  • Background or research in cross-disciplinary areas such as: 
    • Statistical physics, complex systems, or network theory 
    • Applied or computational mathematics 
    • Machine learning or probabilistic modeling 
    • Quantum computing or advanced optimization techniques 
    • Topological data analysis or geometric data methods 
  • Prior research, publications, or project work demonstrating advanced quantitative modeling 
What You’ll Gain
  • Exposure to real-world portfolio risk problems at the intersection of finance and advanced analytics 
  • Opportunity to apply cutting-edge academic methods in a production environment 
  • Collaboration with a highly quantitative, cross-disciplinary team 
  • Experience working with large-scale financial data and modern analytics infrastructure 
  • Mentorship and potential pathway to full-time quantitative roles 
Duration & Compensation
  • Internship: Summer 2026, with potential to extend 
  • Paid internship (competitive, based on experience and location)