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Computer Science Grad Jobs in Pennsylvania (NOW HIRING)

Vanguard

Data Scientist, Specialist

Malvern, PA

Bachelor's degree in Statistics, Applied Mathematics, Computer Science, Economics, Analytics, or a related quantitative field -- or an equivalent combination of training and experience. Grad degree ...

Vanguard Group

Data Scientist, Specialist

Malvern, PA · On-site

Bachelor's degree in Statistics, Applied Mathematics, Computer Science, Economics, Analytics, or a related quantitative field - or an equivalent combination of training and experience. Grad degree ...

The Pennsylvania State University

Students studying Electrical Engineering, Mechanical Engineering, Computer Science, Computer Engineering, Aerospace Engineering, Applied Mathematics, Data Science, or Physics are encouraged to apply.

SynergisticIT

Business Analyst

Philadelphia, PA · On-site

CS Grad, But No Interviews? Let's Change That with SynergisticIT You've put in the hard work. You earned your Computer Science degree, built projects, maybe even applied to dozens--if not hundreds ...

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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 Pennsylvania? For Computer Science Grad jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Computer Science Grad jobs in Pennsylvania look for? The top searched job categories for Computer Science Grad jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Computer Science Grad jobs? Cities in Pennsylvania with the most Computer Science Grad job openings:
Computer Science Grad jobs near you
Infographic showing various Computer Science Grad job openings in Pennsylvania as of June 2026, with employment types broken down into 3% As Needed, 68% Full Time, 21% Part Time, 5% Contract, and 3% Nights. Highlights an 76% Physical, and 24% Remote job distribution.
Data Scientist, Specialist

Data Scientist, Specialist

Vanguard

Malvern, PA

Full-time

Posted 7 days ago

Job description

Performs deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making.

Role Summary 

As a Data Scientist, you will help turn data into decisions by combining strong technical execution with growing business awareness and communication skills. Working alongside more senior data scientists and cross-functional partners, you will contribute to solving real business problems and learn how analytics connects to outcomes. 

You’ll own well-defined components — a model, a feature pipeline, an analysis — while developing the ability to understand stakeholder needs, ask the right questions, and explain your work clearly so others can act on it. The problems will often arrive partially framed; your role is to execute rigorously while building the judgment to connect technical outputs to business value. 

This is a hands-on, growth-oriented role on cross-functional teams where you’ll build both technical depth and the communication skills needed to become a trusted analytics partner over time. 

What You’ll Do 

Explain your work clearly to technical and non-technical teammates. Communicate methods, results, and limitations so findings are understood, trusted, and usable in decision-making. 

Build well-scoped models and analyses. Develop and validate models on defined problems such as feature engineering, model fitting, calibration, and validation with guidance on approach and standards. 

Wrangle and prepare data. Access, transform, clean, and document large-scale data; identify and diagnose inconsistencies and gaps. 

Contribute to production. Help deploy and monitor models alongside MLE and engineering, learning the discipline of keeping a live model healthy. 

Run experiments others design. Execute designed experiments and analyses correctly and interpret the results. 

Explain your work clearly. Communicate methods, results, and caveats to your team so findings can be trusted and built on. 

Use AI to work faster. Apply AI coding and analysis assistants to accelerate your own work, while learning to evaluate their output critically. 

Learn the practice. Absorb standards and patterns from senior teammates and contribute to a growing, AI-native analytics community. 

Core Qualifications 

  • 3+ years of data science / ML experience  

  • Bachelor’s degree in Statistics, Applied Mathematics, Computer Science, Economics, Analytics, or a related quantitative field — or an equivalent combination of training and experience. Grad degree preferred. 

  • Working proficiency in Python and SQL and comfort wrangling real, messy data. 

  • Solid foundation in statistical and machine learning methods and an understanding of model validation. 

  • Exposure to cloud environments (AWS, Azure, or GCP) and standard tooling (e.g., Git, Jupyter). 

  • Clear communication and a strong desire to learn. 

Building for the Age of AI 

We expect this role to use modern AI tools fluently and to grow into building with them. Strength or genuine curiosity in several of the following is what we’re looking for: 

  • Working with GenAI / LLMs: comfort using retrieval-augmented generation (RAG), embeddings, and prompting following established patterns. 

  • Building alongside agentic systems: contributing to LLM/agent workflows that someone more senior has architected. 

  • Evaluation basics: helping test model and LLM output against defined quality metrics. 

  • Experimentation fundamentals: understanding the difference between what predicts an outcome and what changes it. 

  • AI-augmented working style: using AI coding assistants to move faster while sanity-checking their output rather than trusting it by default. 

Preferred / Nice to Have 

  • Project or coursework experience with recommendation, ranking, or decision-support problems. 

  • Familiarity with notebooks-to-production workflows and version control. 

  • Exposure to big-data frameworks (Spark, etc.). 

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

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