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Intern Nba Computer Science Jobs in Boston, MA (NOW HIRING)

Intern, Engineering

Marlborough, MA · On-site

$17.25 - $22.50/hr

The Engineering Intern will support the team by working with SBO crystal imaging data, including ... Must be enrolled in an engineering, computer science, physics, or related technical degree program

The intern will work closely with experienced engineers, gaining exposure to real-world software ... Currently pursuing a Bachelor's degree in Computer Science, Software Engineering, or a related ...

Help Desk Technician Intern

Framingham, MA · On-site

$16.25 - $21.75/hr

Help Desk Technician Intern Department: Technology Reports to: VP, Director of Information ... Currently enrolled in a computer science, information technology, or related degree program

New

IT Intern

Boston, MA · Hybrid

$22 - $24/hr

POAH is seeking an IT Intern to join its IT Department for the spring (PT) and summer of 2024 ... on Computer Science or Information Technology. Candidates should have a working knowledge of ...

Pine Street Inn is seeking a motivated IT Support Intern for a three-to-six-month term to assist ... Computer Science, or a related field * Prior experience in a technical support or desktop ...

IT Support Intern

Boston, MA · On-site

$20 - $25/hr

Pine Street Inn is seeking a motivated IT Support Intern for a three-to-six-month term to assist ... Computer Science, or a related field * Prior experience in a technical support or desktop ...

FSQA Internship

Gloucester, MA · On-site

$20 - $25/hr

... the intern responsibilities will be linked to Gorton's current business strategies, and the ... Computer Science - Must be willing to taste fish and shellfish prototypes, with the ability to ...

Software Developer Intern Reports to: Product Development Leader FLSA Status: Non-Exempt Job ... Pursuing a BS or MS in Computer Science, Computer Engineering, or related field * Strong foundation ...

Intern - Controls Engineering Schedule: Part Time (June-August) Location: Beverly, MA *To support ... Computer Science, or a related field. * Ability to work onsite in the Beverly, MA area. * Strong ...

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Showing results 1-20

Intern Nba Computer Science information

What is the difference between Intern Nba Computer Science vs Intern Data Analyst?

AspectIntern Nba Computer ScienceIntern Data Analyst
Required CredentialsComputer Science coursework, programming skillsStatistics, data analysis skills, some programming
Work EnvironmentTech teams, software development, data managementData teams, reporting, data visualization
Employer & Industry UsageSports organizations, tech companies, NBA teamsBusiness, marketing, sports analytics firms
Common Search & ComparisonYesYes

The Intern Nba Computer Science role focuses on software development, programming, and technical projects within the NBA environment, often involving data management and tech solutions. In contrast, the Intern Data Analyst role emphasizes analyzing data, creating reports, and visualizations to support decision-making. Both internships require analytical skills, but the Computer Science position leans more toward coding and technical tasks, while Data Analyst roles focus on interpreting data and insights.

What cities near Boston, MA are hiring for Intern Nba Computer Science jobs? Cities near Boston, MA with the most Intern Nba Computer Science job openings:
Infographic showing various Intern Nba Computer Science job openings in Boston, MA as of May 2026, with employment types broken down into 67% Part Time, and 33% Temporary. Highlights an 67% In-person, and 33% Remote job distribution.

Ph.D. Graduate Intern Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA

Full-time

Posted 22 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 applyespecially 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 Youll 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)