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Entry Level Computer Science Graduate Jobs in Massachusetts

IBM

Quantum algorithm theorist

Cambridge, MA · On-site

$127.80K - $157.50K/yr

... computer science. • Postdoctoral research experience or completion of a graduate program with substantial focus on quantum algorithms, quantum complexity theory, or related areas. Company : IBM ...

MIT Human Resources

Human Resources Assistant

Cambridge, MA · On-site

$41K - $52.50K/yr

... in the MIT's Computer Science and Artificial Intelligence Laboratory of over 1400 faculty, staff, postdocs, and students. Will be responsible for overseeing both graduate and undergraduate ...

The Hollister Group

Data Scientist - NYC

Boston, MA · On-site

$100 - $200/hr

... data science field (Computer Science, Statistics, Mathematics, Finance, etc.) or equivalent ... entry-level data science concepts) * Experience writing code in Python * Experience handling ...

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Entry Level Computer Science Graduate information

What are the key skills and qualifications needed to thrive as an Entry Level Computer Science Graduate, and why are they important?

To thrive as an Entry Level Computer Science Graduate, you need foundational knowledge in programming languages (such as Python, Java, or C++), algorithms, and data structures, supported by a bachelor's degree in computer science or a related field. Familiarity with version control systems like Git, basic database management, and exposure to development tools or cloud platforms is often expected. Strong problem-solving abilities, teamwork, and effective communication skills help you collaborate and adapt within dynamic environments. These skills and qualities enable you to efficiently contribute to software projects, learn new technologies quickly, and work productively within engineering teams.

What types of projects or tasks can an entry level computer science graduate expect to work on during their first year?

As an entry level computer science graduate, you can expect to work on a variety of tasks such as debugging software, writing code for smaller features, assisting with testing and quality assurance, and supporting senior developers on larger projects. You may also participate in code reviews, maintain documentation, and collaborate closely with team members from development, QA, and product management. These responsibilities are designed to help you build technical proficiency, familiarize yourself with company tools and processes, and gain experience working in a professional software development environment.

What are entry level computer science graduates?

Entry level computer science graduates are individuals who have recently completed a degree in computer science and are beginning their professional careers. They typically possess foundational knowledge in programming, algorithms, data structures, and software development. These graduates often seek positions such as junior software developer, IT support specialist, or QA tester. Employers look for candidates who can demonstrate problem-solving skills, a willingness to learn, and the ability to work effectively in a team.

What is the difference between Entry Level Computer Science Graduate vs Software Developer?

AspectEntry Level Computer Science GraduateSoftware Developer
Required CredentialsBachelor's in Computer Science or related fieldBachelor's in Computer Science or related field; coding skills
Work EnvironmentInternships, entry-level roles, training programsDevelopment teams, tech companies, startups
Employer & Industry UsageUniversities, tech firms, government agenciesSoftware companies, IT departments, tech startups
Common Search/ComparisonYesYes

Entry Level Computer Science Graduates typically possess foundational knowledge and may be in internships or entry roles, focusing on learning and skill development. Software Developers build on this foundation, actively creating and maintaining software applications in professional environments. While both roles require similar educational backgrounds, Software Developers usually have more practical coding experience and responsibilities.

What are the most commonly searched types of Computer Science Graduate jobs in Massachusetts? The most popular types of Computer Science Graduate jobs in Massachusetts are:
What are popular job titles related to Entry Level Computer Science Graduate jobs in Massachusetts? For Entry Level Computer Science Graduate jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Entry Level Computer Science Graduate jobs in Massachusetts look for? The top searched job categories for Entry Level Computer Science Graduate jobs in Massachusetts are:
What cities in Massachusetts are hiring for Entry Level Computer Science Graduate jobs? Cities in Massachusetts with the most Entry Level Computer Science Graduate job openings:
Entry Level Computer Science Graduate jobs near you

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Posted 23 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)