AI & Data Science Intern

Description Position Overview We are seeking intellectually curious and technically driven AI & Data Science Interns to join our Federal Practice team. In this role, you will work alongside experienced data scientists, machine learning engineers, and federal agency partners to design and deploy AI-powered solutions that address real-world government mission challenges — from national security and public health to financial oversight and citizen services. This is not a "shadow and observe" internship. You will contribute meaningfully to project delivery, develop production-quality work products, and leave with a portfolio of federal mission impact you can speak to directly This is an unpaid internship designed as a launchpad for high performers, with top candidates having the opportunity to earn a paid position based on their impact and growth. --- Key Responsibilities Apply AI/ML techniques to structured and unstructured federal datasets, including NLP, computer vision, time-series forecasting, anomaly detection, and classification models Develop and iterate on data pipelines to ingest, clean, transform, and analyze large-scale government datasets (e.g., procurement data, case management records, sensor feeds) Prototype and evaluate large language model (LLM) applications , including retrieval-augmented generation (RAG), prompt engineering, and agentic workflows tailored to agency use cases Translate mission requirements from federal agency stakeholders into technical problem statements and data-driven solution approaches Build dashboards and data visualizations to communicate analytical findings to both technical and non-technical government audiences Support responsible AI practices by contributing to model documentation, bias assessments, and explainability frameworks in compliance with federal AI governance standards (e.g., OMB

M-24-10, EO 14179

) Collaborate in agile teams , participate in sprint planning, demos, and retrospectives, and contribute to technical documentation and knowledge management Present findings to internal teams and, where appropriate, to federal agency stakeholders Requirements Currently enrolled in an accredited Bachelor's, Master's, or PhD program in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field Minimum GPA of 3.2/4.0 (or equivalent) Proficiency in Python and common data science libraries (pandas, NumPy, scikit-learn, Matplotlib/Seaborn) Familiarity with machine learning fundamentals : supervised/unsupervised learning, model evaluation, feature engineering Experience working with SQL or other data querying languages Strong analytical thinking and ability to frame ambiguous problems into tractable analytical approaches Excellent written and verbal communication skills; ability to explain technical concepts to non-technical stakeholders --- Preferred Qualifications Experience with deep learning frameworks (PyTorch, TensorFlow, Hugging Face Transformers) Hands-on exposure to LLMs and generative AI applications (prompt engineering, fine-tuning, RAG pipelines, agentic frameworks such as LangChain or AutoGen) Familiarity with cloud platforms (AWS GovCloud, Azure Government, or Google Cloud) and MLOps tooling (MLflow, SageMaker, Vertex AI) Experience with data visualization tools (Tableau, Power BI, Plotly Dash, or similar) Knowledge of federal data sources (USASpending, Data.gov, Census Bureau APIs, or agency-specific systems) Prior internship, research, or project experience in a government, defense, or public sector context Completion of coursework or projects in AI ethics, responsible AI, or AI policy What You'll Gain Mission-driven impact: Your work will directly support federal agencies tackling challenges in areas such as fraud detection, workforce analytics, supply chain resilience, public health surveillance, and more Technical depth: Hands-on experience applying cutting-edge AI/ML methods to complex, real-world datasets — not toy problems Federal domain expertise: Exposure to the federal acquisition, compliance, and program environment that shapes how AI is deployed in government

Mentorship:

Paired with a senior data scientist or ML engineer who will provide technical guidance and career coaching throughout the internship Professional development: Access to internal learning resources, industry certifications (AWS, Azure, Google Cloud), and speaker series Pathway to full-time: High-performing interns are considered for full-time associate and analyst roles upon graduation