Consultative Offerings - Analyst - Data & AI Solutions Engineering

Build agentic workflows powered by AI that act autonomously with human oversight—helping clients automate, analyze, and adapt.

Design and deploy generative-AI solutions, such as copilots, assistants, and intelligent content generation tools using large language models (LLMs).

Serve as a Forward Deployed Engineer: embed with client teams to understand real-world challenges, co-create tailored AI solutions, and ensure production-grade implementation.

Shape strategy and execution: You’ll do more than model—you’ll help clients transform how they operate with AI embedded in their core workflows.

Translate business needs into technical architectures using cloud platforms, APIs, ML models, and modern DevOps tooling.

Innovation and Critical Thinking

Apply structured problem-solving and systems thinking to navigate ambiguity and uncover impactful insights.

Challenge assumptions, propose new solutions, and take initiative in designing scalable AI/analytics systems.

Generative AI& Applied Intelligence

Develop and fine-tune generative AI models (e.g., LLMs, diffusion models) for use cases like summarization, reasoning, content generation, and conversational agents.

Design prompt engineering workflows and retrieval-augmented generation (RAG) pipelines to support real-time decisioning and contextual understanding.

Implement monitoring, evaluation, and governance frameworks for AI/ML models in production.

Data Engineering & Infrastructure

Build and optimize robust data pipelines using tools like SQL, Python, Apache Spark, Airflow, and cloud-native services.

Design data architectures that support scale, real-time insights, and cross-functional AI workloads.

Implement ELT/ETL processes that ensure data quality, lineage, and observability.

Forward Deploy Engineering

Operate in agentic client environments, embedding directly with client teams to rapidly prototype, iterate, and deploy solutions.

Translate business challenges into technical specifications and lead solution delivery from concept to production.

Interface directly with business and engineering stakeholders, driving impact in highly visible engagements.

Collaboration & Communication

Communicate complex technical topics clearly to non-technical stakeholders through compelling storytelling and visualization.

Mentor peers and clients on analytics best practices and AI solution adoption, promoting a data-first culture.

Contribute to internal IP, toolkits, and accelerators that help scale AI and data capabilities across industries.

Strong understanding of Windows-based systems and proficiency with Microsoft Excel, Word, and PowerPoint, supporting effective data management and presentation

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

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.

Must be currently enrolled in an accredited college or university and expected to graduate by Spring/Summer 2027 pursuing a bachelor’s degree or higher in one of the following majors or a related/equivalent program:

Computer Science, Data Science, Statistics, Applied Math, Data Analytics, Management Information Systems, Economics, Finance, Business Analytics, Mathematics, Engineering, or a related field, with relevant analytics or data management coursework preferred

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

Must live within a commutable distance to your assigned office (e.g. 100-mile radius) with the ability to commute daily, if required, upon start date

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)