Data Analyst Summer Intern

Vidoori • Hyattsville, MD

2h • Hybrid

About The Position

Vidoori is a leading provider of digital transformation and technology solutions, empowering organisations across multiple industries to accelerate business value and innovation. We are seeking an analytical, curious, and collaborative Data Analyst Summer Intern to join our team for a fixed summer placement. This role is ideal for someone studying Data Science, Statistics, Computer Science, Economics, or a related discipline who wants hands-on experience applying data analysis, modelling, and large language model tools to real-world problems in a technology-led organisation.
Data Analyst Summer Intern – Role Overview
As a Data Analyst Summer Intern, you will support data-driven projects across product, engineering, and business teams. You will work with structured and unstructured data, build reproducible Python-based analysis, apply and evaluate classification and regression methods, and explore the use of large language model (LLM) tools to augment workflows. The placement offers mentorship, practical responsibilities, and exposure to an agile, collaborative environment.

Requirements

• Currently studying towards a degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related field, or recent graduate with relevant coursework.
• Intermediate Python proficiency: has developed at least one complete project using functions, classes, and modules, with readable, modular code and basic testing or documentation.
• Familiarity with classification and regression methods (for example: logistic regression, decision trees, random forests, linear regression, and gradient-boosted methods) and experience implementing them using common libraries (e.g., scikit-learn, XGBoost, LightGBM).
• Understanding of the bias–variance tradeoff and practical methods to avoid overfitting and underfitting (cross-validation, regularisation, feature selection, early stopping, ensembling).
• Familiarity with commercial or open-source LLM tools and a basic understanding of prompt engineering principles to guide model outputs and mitigate common failure modes.
• Comfortable working with data analysis and visualisation tools (Pandas, NumPy, Matplotlib/Seaborn, or equivalents) and willing to learn additional tools and cloud services as required.
• Good written and verbal communication skills with the ability to explain technical concepts to non-technical stakeholders; organised and able to manage time across multiple tasks.
• Respectful of data privacy and security considerations; demonstrates integrity when handling sensitive information.

Responsibilities

• Design and implement end-to-end analysis workflows in Python, producing clean, documented code using functions, classes, and modules.
• Prepare, clean, and transform data from multiple sources to create analysis-ready datasets; apply appropriate feature engineering and exploratory data analysis.
• Develop and evaluate predictive models (classification and regression), using established libraries and techniques; produce clear evaluation metrics and visualisations.
• Demonstrate understanding of bias–variance tradeoff: select suitable model complexity, apply regularisation, cross-validation, and other techniques to avoid overfitting and underfitting.
• Investigate and experiment with commercial or open-source LLM tools to support tasks such as data summarisation, automated reporting, or prototype conversational interfaces; apply basic prompt engineering to improve outputs.
• Document methods, assumptions, and results; present findings to stakeholders and incorporate feedback into iterative analysis.
• Contribute to team knowledge sharing by writing clear code comments, brief technical notes, and participating in peer review.

Benefits

• Fixed-term paid internship with structured objectives, mentoring, and regular feedback to support your development.
• Practical, hands-on experience applying data analysis and modelling to real business problems within a technology-driven company.
• Guidance on good software engineering practices for data projects, reproducible analysis, and model evaluation.
• Exposure to LLM tooling and applied prompt engineering in an operational setting, with opportunities to prototype and iterate.
• Flexible working arrangements and a collaborative team culture that values inclusion, curiosity, and continuous learning.

What This Job Offers

• Career Level: Intern