Business Analyst acting as a critical link between business and technical teams at Vodafone. Involves gathering requirements and ensuring technical specifications in telecom projects.
About the role
- Data Science & Analytics Intern developing data-driven insights and models for business stakeholders. Supporting technical model development and business analytics in Financial Planning and Analysis.
Responsibilities
- Perform quantitative and exploratory analysis across business and financial domains, including data mining, statistical analysis, and model development
- Translate ambiguous business questions into structured analytical approaches, data pipelines, and model frameworks
- Generate and test hypotheses using appropriate statistical, econometric, or experimental designs and extract actionable insights
- Develop, train, evaluate, and maintain predictive and machine learning models (regression, classification, clustering, time series, etc.)
- Support the design and development of Generative AI solutions and AI agents using Large Language Models (LLMs)
- Assist in building end-to-end data pipelines, from data ingestion and preparation to modeling, validation, and deployment
- Produce analytical reports, dashboards, and visualizations that highlight trends, drivers, and performance against KPIs
- Convert technical findings into clear, business-ready narratives and recommendations for senior leadership
- Partner with business stakeholders to present insights, answer questions, and support decision-making
- Document methodologies, assumptions, results, and recommendations to ensure transparency and reusability
- Identify opportunities for process improvement, automation, and advanced analytics across the organization
- Demonstrate willingness to learn new tools, technologies, and techniques in a rapidly evolving analytics environment
Requirements
- Currently pursuing a BA/BS or MS in Economics, Statistics, Data Science, Computer Science, Mathematics, or another quantitative discipline
- Strong foundation in statistics, econometrics, experimental design, and analytical problem-solving
- Ability to flex between Data Science (modeling, ML, AI) and Analytics (EDA, reporting, insights) based on business needs
- Proficiency in Python or R, with experience using libraries such as pandas, scikit-learn, TensorFlow, PyTorch, PySpark, or similar
- Experience with data querying and manipulation using SQL
- Familiarity with cloud and data platforms such as Azure ML, Snowflake, or Google Analytics
Benefits
- Medical/Dental/Vision
- 401 (k) match
- PTO starting at 3 weeks' vacation + (7) paid holidays and (5) personal days
- Employer-paid life insurance
- Tuition reimbursement
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