Data & AI Solutions Engineering Summer Scholar Intern

Are you ready to go beyond your potential and reach something greater? At Deloitte, we believe in more than just growth—we believe in exponential possibilities. Here, your unique talents and ambitions are amplified by the power of our collaborative teams, innovative thinking, and mentorship. When you join Deloitte, you don’t just build a career—you unlock unlimited opportunities, shaping your future and the world around you. Take the power of you and put it to the power of Deloitte. Reach your exponential!

Recruiting for this role ends on 11/01/2026.

Work You’ll Do

As a Data & AI Solutions Engineering Summer Scholar, you won’t just write code or build dashboards—you’ll solve some of the most pressing business and societal challenges of today using data, intelligence, and creativity. We’re looking for individuals who think critically, act boldly, and are ready to take ownership in fast-moving environments.

You’ll work at the intersection of AI engineering, data infrastructure, and forward deployment, contributing to client solutions that go beyond analysis and into activation, building data-driven solutions with speed, scale, and substance. You won’t stop at insights — you’ll operationalize intelligence through platforms, automation, and integrated deployment. From designing agentic workflows that automate decision-making to building pipelines that fuel generative AI models, you’ll be empowered to think like an entrepreneur and deliver like an engineer.

Curious what this might look like in action? Our Data & AI Solutions Engineering Summer Scholars engage in the following types of work… 

AI & Engineering - Responsible for leveraging the power of data and artificial intelligence (AI) to inform data-driven decisions at various levels, including providing insights from data using computational and AI-driven analyses and processes to support data-driven decision making as well as developing and maintaining measurement solutions and capabilities. 

Advertising, Marketing & Commerce - Responsible for supporting clients in enabling and transforming business processes through technology, but can also leverage data management, analytics, and AI to solve marketer-focused business challenges across a variety of domains by using quantitative and qualitative data analytics, that contribute to comprehensive research, statistical analysis, and data management.  

Regulatory Risk & Forensic -Responsible for architecting risk-based technology and analytics, analyzing enterprise organization risks, and delivering platform requirements for mitigation. Supports digital transformation, manages legacy systems, and uses AI/data analysis to design solutions. Provides strategic direction on Data, Modeling, and AI risks, develops governance strategies, and collaborates to align capabilities and expand into new markets.

Strategy & Transactions - Responsible for leveraging scientific problem-solving, applied AI/ML, human-centered design, and data science to diagnose and solve complex, often ambiguous business challenges that have not been solved before, across client domains and industries. Applies analytical rigor and technical depth — not just implementation — to frame the problem, select the right method, and build, evaluate, and communicate solutions that drive innovation and informed decision-making for clients. Demonstrates the curiosity, adaptability, and cross-domain thinking of a scientific generalist, with a genuine passion for applying rigorous problem-solving to real-world challenges.

 
Regardless of project type your work may include:

• Proficiency in scripting languages and data visualization platforms, with the ability to extract, transform, merge, and analyze data sets for actionable business insights

• Solid grasp of the data lifecycle, analytics concepts, and the solutions development process, paired with strong problem-solving and critical thinking skills to drive innovation and operational improvements

• Excellent verbal and written communication skills, along with the ability to work independently, manage multiple projects, and collaborate effectively with Deloitte teams and client stakeholders

• Willingness and ability to learn and implement new concepts, frameworks, and emerging technologies, demonstrating a commitment to ongoing personal and professional development

What Makes You Stand Out

• Agentic AI thinking: You’re not just building models—you’re building AI-powered systems that observe, decide, and act with autonomy and alignment.

• Data engineering fluency: You understand that robust, scalable data pipelines and architectures are critical to building performant AI.

• Entrepreneurial energy: You bring initiative, speed, and creativity—crafting MVPs, iterating fast, and thinking like a product owner.

• Forward deployed presence: You thrive in real-time collaboration with client stakeholders, bringing technical ideas to life in their environment.

• Critical and systems thinking: You see the big picture, reason through tradeoffs, and architect holistic solutions.

• Deployment & Governance mindset: You don't just ship agents—you instrument them, knowing when to add human checkpoints, guardrails, and audit trails so autonomy doesn't outpace accountability.

The Team

Our Deloitte team plays a major role in directly embedding technology insights into our clients’ organizational goals. At Deloitte, our consultants create sharply-focused solutions within an organization’s operating model, accounting for its people, intellectual capital, technology, and processes. Engagement teams at Deloitte drive value for our clients but also understand the importance of developing resources and contributing to the communities in which we work. We make it our business to take issue to impact, both within and beyond a client setting. 

Required Qualifications

• Must be currently enrolled in an accredited college or university and expected to graduate by {completed by Spring/Summer 2028} or have completed a bachelor’s degree or higher in Computer Science, Data Science, Statistics, Applied Math, Data Analytics, Management Information Systems, Economics, Finance, Business Analytics, Mathematics, Engineering, or a related/equivalent program

• Strong academic track record (minimum cumulative GPA of 3.0)

• Experience or coursework in data processing and analysis tools (e.g., SQL, Python, R, Power BI, Informatica), and familiarity with analytics, data visualization, or big data platforms (e.g., Tableau, Hadoop, Spark, AWS, Azure, Google Cloud)

• Ability to travel up to 50%, on average, based on the work you do and the clients and industries/sectors you serve

• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

• Candidates must be at least 18 years of age at time of employment

• You must reside within a commutable distance of your assigned office with the ability to commute daily, if required

Preferred Qualifications

• Cumulative GPA of 3.2

• Relevant professional experience, such as internships or part-time roles in analytics, data science, or related fields

• Hands-on experience with LLMs, vector databases, or generative AI APIs (e.g., OpenAI, Claude, Cohere).

• Knowledge of MLOps, CI/CD, and model deployment strategies.

• Internship or project experience in analytics, software engineering, or AI.

• Demonstrated leadership in campus orgs, startups, open-source contributions, or volunteer initiatives.

• Familiarity with a range of analytics, programming, and cloud tools (e.g., SQL, Python, R, Java, Tableau, Power BI, Hadoop, Spark, AWS, Azure, Google Cloud, machine learning frameworks such as TensorFlow or PyTorch)

This is an entry-level opportunity intended for candidates interested in beginning or building a career in this field. We welcome applicants from a range of educational and professional backgrounds who meet the qualifications for the role. For roles that require a year or more of work experience, please review the experienced jobs within our careers site.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.  The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled.  At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.  A reasonable estimate is $48/hour.