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Contractual Computer Science Graduate Jobs in Addison, IL

The School of Computing (SoC) offers a variety of undergraduate and graduate programs including Computer Science, Artificial Intelligence, Cybersecurity, Data Science, Game Programming, Health ...

... scientific and research environment. This position offers an excellent opportunity to develop ... Basic computer proficiency is appropriate for the assigned role. Work Arrangement: Please note that ...

DePaul's graduate and undergraduate Computer Science programs are the premier training ground for computing professionals in the Chicago area. Our M.S. program in Computer Science includes one ...

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Contractual Computer Science Graduate information

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

AspectContractual Computer Science GraduateSoftware Developer
Required CredentialsDegree in Computer Science or related field, possibly internship experienceDegree often preferred; certifications like Java, Python, or cloud certifications beneficial
Work EnvironmentTemporary or project-based roles, often in tech firms or consultingFull-time or freelance roles in tech companies, startups, or agencies
Employer & Industry UsageUsed by companies hiring interns or short-term project staffCommonly employed in software development projects across industries

While both roles involve computer science skills, a Contractual Computer Science Graduate typically works on temporary projects or internships, focusing on gaining experience. In contrast, a Software Developer usually holds a more permanent position, actively developing software products or solutions. The roles overlap in skills but differ mainly in employment type and career stage.

What cities near Addison, IL are hiring for Contractual Computer Science Graduate jobs?

Cities near Addison, IL with the most Contractual Computer Science Graduate job openings:

Talent Community | Data Scientist

EVOZYNE INC

Chicago, IL • On-site

Full-time

Re-posted 7 days ago


Job description

Evozyne designs and builds engineered protein therapeutics using our AI-native platform, transforming what’s possible in immune-mediated disease treatment. Our Data Scientists partner closely with our research teams to transform complex experimental data into insights that guide molecule design and program strategy, turning bold ideas into therapies that can meaningfully improve patients’ lives. This posting helps us connect with candidates for future opportunities. While this listing is not tied to a current opening, we encourage you to join our talent community so we can connect with you when new roles emerge!

Key Responsibilities

  • Analyze and integrate diverse experimental datasets (e.g., sequencing, biophysical, cell-based, and functional assays) to inform therapeutic design decisions
  • Develop computational and statistical models to support protein engineering, optimization, and candidate selection
  • Design and implement workflows for data processing, visualization, and interpretation that enable rapid, high-quality decision-making
  • Partner with discovery scientists to translate biological questions into quantitative analyses and predictive approaches
  • Apply machine learning and modeling methods to improve design strategies
  • Build scalable tools and pipelines that enhance reproducibility and accessibility of experimental insights
  • Communicate findings clearly to cross-functional teams and contribute to project strategy and prioritization

Who You Are

You thrive in an early-stage start-up environment and are motivated by the opportunity to build new therapies that can transform patients’ lives. You combine agility with scientific rigor to deliver high-quality results, and you bring natural curiosity and a collaborative mindset to solving complex challenges.

Minimum Qualifications

  • Undergraduate and/or graduate level education focused on data science, computational biology, bioinformatics, computer science, machine learning, AI, or a similar field
  • Hands on experience analyzing experimental, biological, chemistry, or physics datasets (industry, startup, or academic lab)
  • Ability to understand experimental context (read protocols, interpret assay outputs) and partner effectively with experimentalists
  • Solid grasp of EDA and basic statistics (distributions, confidence intervals, hypothesis testing)