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Computer Science Grad Jobs in New York, NY (NOW HIRING)

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Staff Solutions Engineer, Level 6

New York, NY · On-site

... grad software development or solutions engineer experience * Experience coding and building ... Advanced degree in computer science or computer engineering * Highly proficient in JavaScript (and ...

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Computer Science Grad information

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

To thrive as a Computer Science Graduate, you need a solid understanding of programming languages, algorithms, data structures, and fundamental computer science concepts, typically gained through a bachelor's degree in computer science or a related field. Familiarity with development environments, version control systems like Git, and frameworks relevant to your specialization is often expected. Problem-solving, teamwork, and strong communication skills help you collaborate efficiently and adapt to evolving project requirements. These skills and qualities are crucial for building robust software solutions and succeeding in dynamic technology-driven workplaces.

What are Computer Science grads?

Computer Science grads are individuals who have completed a degree program in computer science, typically at the undergraduate or graduate level. They possess knowledge and skills in areas such as programming, algorithms, data structures, software engineering, and computer systems. These graduates are equipped to pursue careers in various tech fields including software development, data analysis, cybersecurity, and more. Their education often includes both theoretical foundations and practical experience with modern technologies.

What are some common entry-level positions for recent computer science graduates, and how do they typically collaborate within a team?

Recent computer science graduates often start in roles such as software engineer, QA analyst, IT support specialist, or junior web developer. In these positions, you'll usually work as part of a project team alongside more experienced engineers, designers, and sometimes product managers. Collaboration is key—you'll participate in code reviews, daily stand-up meetings, and pair programming sessions to learn best practices and contribute to shared goals. This team-oriented environment not only helps build technical skills but also offers mentorship opportunities and exposure to different aspects of software development.

What is the difference between Computer Science Grad vs Software Developer?

AspectComputer Science GradSoftware Developer
CredentialsDegree in Computer Science or related fieldOften requires a degree, but certifications and experience can suffice
Work EnvironmentAcademic settings, internships, entry-level rolesCorporate offices, tech companies, startups
Industry UsageEducational institutions, entry-level tech rolesProduct development, application building, coding tasks
Search & Comparison IntentEntry-level, educational background, career startPractical coding, project work, job opportunities

While a Computer Science Grad typically refers to someone with a degree in computer science, a Software Developer is a professional actively involved in coding and building software applications. Many Computer Science Grads pursue roles as Software Developers, but the latter emphasizes practical skills and work experience. Understanding this difference helps job seekers target the right roles and employers effectively.

What are popular job titles related to Computer Science Grad jobs in New York, NY? For Computer Science Grad jobs in New York, NY, the most frequently searched job titles are:
What job categories do people searching Computer Science Grad jobs in New York, NY look for? The top searched job categories for Computer Science Grad jobs in New York, NY are:
What cities near New York, NY are hiring for Computer Science Grad jobs? Cities near New York, NY with the most Computer Science Grad job openings:
Computer Science Grad jobs near you
Infographic showing various Computer Science Grad job openings in New York, NY as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 82% Physical, 1% Hybrid, and 17% Remote job distribution.

New Grad Full-Time Quantitative Researcher

WallStreetQuants

New York, NY • On-site

Full-time

This job post has expired 3 days ago. Applications are no longer accepted.

Job description

About the Role

An NYC based hedge fund is seeking a highly motivated and intellectually curious New Grad Quantitative Researcher to join the team full time. This role is ideal for recent graduates who enjoy solving complex problems using mathematics, statistics, programming, and data-driven analysis.

As a Quantitative Researcher, you will work at the intersection of financial markets, statistical modeling, and technology. You will collaborate with traders, developers, and other researchers to identify patterns in market data, develop predictive models, test trading hypotheses, and support the creation of quantitative strategies.

This is an excellent opportunity for a new graduate who is analytical, creative, and excited to apply rigorous research methods to real-world financial markets.

Requirements

Responsibilities
  • Conduct quantitative research to identify signals, patterns, and inefficiencies in financial markets.
  • Analyze large and complex datasets, including market data, alternative data, and time-series data.
  • Develop, test, and refine statistical models, predictive signals, and trading strategies.
  • Design and run backtests, simulations, and experiments to evaluate research ideas.
  • Collaborate with traders and developers to translate research findings into production-ready tools and strategies.
  • Monitor model performance and contribute to ongoing strategy improvement.
  • Apply techniques from statistics, machine learning, optimization, probability, and econometrics to solve trading-related problems.
  • Present research findings clearly to technical and non-technical stakeholders.
  • Stay current on market behavior, quantitative methods, and emerging research relevant to trading and investing.
Qualifications
  • Recent graduate or upcoming graduate from a Bachelor’s, Master’s, PhD, or equivalent program.
  • Degree or strong demonstrated experience in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Physics, Economics, Finance, Data Science, Operations Research, or a related discipline.
  • Strong foundation in probability, statistics, linear algebra, optimization, or machine learning.
  • Programming experience in Python, R, C++, Java, Julia, MATLAB, or a similar language.
  • Experience working with data through coursework, research, internships, projects, or independent study.
  • Strong analytical thinking, problem-solving ability, and attention to detail.
  • Ability to communicate complex ideas clearly and work collaboratively across teams.
  • Interest in financial markets, trading, investing, or data-driven decision-making.
Preferred Qualifications
  • Research, internship, or project experience involving statistical modeling, machine learning, time-series analysis, forecasting, optimization, or quantitative finance.
  • Experience with Python data science libraries such as pandas, NumPy, SciPy, scikit-learn, PyTorch, TensorFlow, or statsmodels.
  • Familiarity with SQL, large-scale data processing, cloud tools, or distributed computing.
  • Exposure to financial instruments such as equities, futures, options, fixed income, FX, commodities, or digital assets.
  • Experience with backtesting, simulation, portfolio construction, or risk modeling.
  • Participation in math competitions, programming competitions, research publications, Kaggle, hackathons, trading competitions, poker, chess, or other analytical competitions.

Benefits

What We Offer
  • Full-time role designed for new graduates.
  • Structured training and mentorship from experienced quantitative researchers, traders, and engineers.
  • Opportunity to work on impactful research used in real-time trading and investment decisions.
  • Exposure to financial markets, strategy development, data science, and trading infrastructure.
  • A collaborative, intellectually rigorous environment where research quality and strong ideas are valued.
  • Early ownership of meaningful research projects.
  • Competitive compensation and benefits.