Opportunities

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Students are required to include a cover letter outlining their fit for the position they are applying.

Accounting Intern – Summer 2025 - JobID: 3

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Position Summary

DSRS is seeking a highly motivated and detail-oriented Accounting Intern to support our financial operations and contribute to cost-efficiency initiatives. This role offers a hands-on opportunity to learn about budgeting, procurement, and financial coordination within a dynamic research and development environment. The ideal candidate will be proactive, organized, and interested in gaining practical experience in nonprofit or academic financial systems.

Key Responsibilities

Review and catalog all organizational purchases, grants, subscriptions, and awards.
Identify and document internal stakeholders responsible for financial activities, including budget oversight.
Analyze current expenses and provide recommendations for cost-saving opportunities.
Coordinate with internal staff to streamline purchasing workflows and maintain cordial relationships.
Support vendor negotiations to ensure favorable pricing for both DSRS and its partners.
Assist with general accounting tasks and financial documentation.
Contribute to additional finance-related projects as needed.

Qualifications

Must be a currently enrolled student with at least one academic semester remaining prior to graduation.
Pursuing a degree in Accounting, Finance, Business Administration, or related field.
Strong proficiency in Microsoft Excel or Google Sheets; familiarity with accounting tools is a plus.
Excellent organizational, analytical, and interpersonal skills.
Ability to work independently and communicate effectively in a remote team setting.

Marketing Communications Intern– Summer 2025 - JobID: 4

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Position Summary

DSRS is looking for a dynamic and self-driven Marketing Communications Intern to elevate our digital presence and strengthen stakeholder engagement across channels. This role is ideal for a content-savvy communicator with a passion for storytelling, branding, and digital outreach. Candidates with familiarity in data science or programming concepts are highly encouraged to apply, although this is not a requirement.

Key Responsibilities

Manage and update content on the DSRS website, including news, announcements, and organizational updates.
Develop and schedule content for LinkedIn and other social platforms to increase visibility and engagement.
Craft clear and compelling messaging to promote DSRS’s work to faculty, researchers, staff, and students.
Assist in the development of marketing materials and promotional campaigns.
Ensure brand consistency and tone across all public-facing content.
Collaborate with internal teams to gather content ideas and highlight ongoing projects.
Participate in other marketing and communication initiatives as needed.

Qualifications

Must be a currently enrolled student with at least one academic semester remaining prior to graduation.
Pursuing a degree in Communications, Marketing, Journalism, Public Relations, or a related field.
Excellent written and verbal communication skills.
Strong organizational skills and attention to detail.
Ability to work independently and manage multiple tasks in a remote work environment.

Preferred, but not required:

Knowledge of data science, research communication, or programming to better understand and promote DSRS’s work.
Familiarity with using GitHub repositories

Data Science Intern – Summer 2025 - JobID: 5

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Position Summary

As a Data Science Intern, you will be at the forefront of designing, developing, and deploying end-to-end data-driven solutions. This role requires a unique blend of strong data science expertise and robust software engineering skills. You will transform complex datasets and analytical models into functional, scalable applications. Collaborating closely with researchers, faculty, and fellow interns, you will not only uncover valuable insights but also build the tools and systems to operationalize them. This is an exceptional opportunity to apply and expand your full-stack data science and software development capabilities on meaningful, research-driven projects.

Key Responsibilities

Collect, clean, and preprocess complex datasets from diverse sources to ensure accuracy, consistency, and suitability for analysis and model training.
Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies, informing model development and strategy.
Develop, train, validate, and implement machine learning models and statistical analyses to address research questions and generate actionable insights.
Design, build, and maintain scalable software applications or tools that integrate data analysis and machine learning models.
Package data science solutions and manage deployment processes.
Implement robust version control practices and contribute to CI/CD pipelines where applicable.
Write clean, efficient, well-documented, and tested code following software engineering best practices.
Collaborate with stakeholders to understand requirements and translate them into effective technical solutions.
Communicate complex technical concepts, methodologies, and findings clearly to both technical and non-technical audiences.
Stay current with new trends and advancements in data science, machine learning, and software engineering, recommending innovative approaches.
Document model methodologies, code structure, and deployment procedures thoroughly.

Qualifications

Must be a student currently enrolled at the University of Illinois, Urbana-Champaign.
Must have an expected graduation date of May 2026 or later.
Strong Python programming skills.
Solid understanding and practical experience with software development principles and practices, including version control.
Demonstrable experience or strong interest in packaging code and deploying applications/models.
Proficiency in statistical analysis and methodologies.
Experience with data cleaning, preprocessing, and feature engineering.
Familiarity with database technologies.
Excellent problem-solving skills with the ability to tackle complex, ambiguous challenges.
Strong attention to detail and the ability to work independently with minimal supervision.
Effective communication skills, capable of explaining technical details and outcomes.

Preferred Qualifications

A background in Computer Science, Data Science, Statistics, or a closely related field.
Strong foundation in machine learning concepts, algorithms, and evaluation techniques.
Familiarity with cloud platforms.

Data Visualization Analyst (Volunteer) – Fall Semester Recruitment (Extended Deadline: 10/18/2024)

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Position Overview:

As a Data Visualization Analyst (Volunteer), you will be instrumental in analyzing complex datasets and transforming them into clear, impactful visualizations. Collaborating with researchers, faculty, and fellow interns, you will help uncover valuable insights and create compelling visual representations. This is an excellent opportunity to apply your analytical and visualization expertise while contributing to meaningful, research-driven projects.

Key Responsibilities:

Collect, clean, and preprocess data from various sources to ensure accuracy and consistency.
Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies in data.
Analyze datasets and generate actionable insights using statistical methods and data analysis techniques.
Develop and maintain dashboards and reports to track key performance indicators (KPIs) and metrics.
Utilize data storytelling techniques to communicate findings in an engaging and meaningful way.
Implement best practices in data visualization to ensure clarity, accuracy, and accessibility.
Stay current with new trends and advancements in data analysis and visualization, recommending innovative solutions where applicable.
Document visualization processes and methodologies to ensure reproducibility and ease of collaboration.

Qualifications:

Must be a student currently enrolled at the University of Illinois, Urbana-Champaign.
Familiarity with data analysis tools and programming languages such as Python, or R.
Proficiency in data visualization tools such as Tableau, or Power BI.
Strong understanding of statistical techniques and methodologies.
Experience with data cleaning and preprocessing techniques.
Strong problem-solving skills with the ability to interpret complex data in a clear and meaningful way.
Strong attention to detail and ability to work with minimal supervision.
Good communication skills, with the ability to present data findings to non-technical stakeholders.
A background in data science, statistics, or a related field is preferred.

Benefits:

Gain hands-on experience in data analysis and visualization in an academic research setting.
Contribute to high-impact projects and research initiatives.
Fully remote with flexible work hours.
Opportunity to network with researchers, faculty, and data science professionals.

Machine Learning Engineer (Volunteer) – Fall Semester Recruitment (Extended Deadline: 10/18/2024)

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Position Overview:

As a Machine Learning Engineer, you will have the opportunity to work closely with researchers, faculty, and fellow interns to implement machine learning solutions for complex research problems. This is an excellent chance to apply your ML skills in a real-world academic setting and contribute to cutting-edge research that drives innovation.

Key Responsibilities:

Collaborate with researchers to design, develop, and implement machine learning models and algorithms.
Assist in the preparation and processing of large datasets for training and testing purposes.
Optimize models for performance, scalability, and deployment in research environments.
Provide technical support for research teams in terms of data acquisition, pre-processing, and computational infrastructure.
Stay updated with the latest machine learning techniques, tools, and trends.
Document processes, methodologies, and findings for use by the research community.

Qualifications:

Must be a student currently enrolled at the University of Illinois, Urbana-Champaign.
Experience in machine learning and data science techniques (e.g., supervised/unsupervised learning, deep learning, reinforcement learning).
Proficiency in Python and machine learning frameworks such as TensorFlow, Keras, PyTorch, or Scikit-learn.
Knowledge of data processing libraries such as Pandas and NumPy.
Strong analytical and problem-solving skills with the ability to interpret complex data.
Familiarity with business data or an interest in applying machine learning to business research is a plus.
Ability to work independently and in a team environment.
Strong communication skills for collaborating with non-technical stakeholders.
A background in data science, statistics, or a related field is preferred.

Benefits:

Gain hands-on experience with real-world machine learning applications in an academic research setting.
Opportunity to contribute to high-impact projects and research publications.
Fully remote with flexible work hours.
Networking opportunities with researchers, faculty, and data science professionals.