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Internship Competitive Analysis Jobs (NOW HIRING)

Get Engaged

Internship

Atlanta, GA · On-site

$14.50 - $19.25/hr

An internship with Get Engaged Media provides students with practical experience in an agency ... competitive analysis of social media profiles, and other activities surrounding social media ...

IQVIA

Key Account Representative

Philadelphia, PA · On-site

Work/internship * Competitive sport * Leadership Have a valid driver's license and be insurable 25 ... Demonstrated analytical skills * Demonstrated success in persuasion, influence, and negotiation ...

Navier

MBA Internship

Alameda, CA · On-site +1

$17 - $22.75/hr

Navier is seeking a highly motivated MBA Interns to support our strategy, product, and growth ... Conduct market research and competitive analyses to identify emerging opportunities in maritime ...

Rag & Bone

Fall 2026 Internship - Social Media

Manhattan, NY · On-site

$16.50 - $21/hr

Fall 2026 Internship - Social Media About rag & bone From our origins in New York in 2002, rag ... Conduct competitive analysis, tracking what peer and aspirational brands are doing across platforms

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How much do internship competitive analysis jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for internship competitive analysis in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What is the difference between Internship Competitive Analysis vs Market Research Intern?

AspectInternship Competitive AnalysisMarket Research Intern
Required CredentialsTypically pursuing or recent graduate in business, marketing, or related fieldsSimilar educational background, often with coursework in marketing, statistics, or social sciences
Work EnvironmentCorporate or consulting firms, marketing departmentsMarket research firms, corporate marketing teams, or consulting agencies
Employer & Industry UsageUsed in competitive intelligence, strategic planning, and marketing analysisUsed for consumer insights, product development, and market trend analysis

Internship Competitive Analysis and Market Research Intern roles share similar educational backgrounds and work environments. However, Internship Competitive Analysis focuses specifically on analyzing competitors' strategies and market positioning, while Market Research Interns gather broader consumer data and market trends. Both roles are essential in strategic decision-making but serve different analytical purposes within the industry.

What cities are hiring for Internship Competitive Analysis jobs? Cities with the most Internship Competitive Analysis job openings:
What are the most commonly searched types of Competitive Analysis jobs? The most popular types of Competitive Analysis jobs are:
What states have the most Internship Competitive Analysis jobs? States with the most job openings for Internship Competitive Analysis jobs include:
Internship Competitive Analysis jobs near you

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Posted 20 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)