Raghav Raheja

Results-driven data analyst with expertise in the end-to-end data journey, from designing robust data infrastructure to delivering well-curated insights to leadership. Detail-oriented and committed to extracting maximum value from data for organizational growth. Experienced in tools ranging from Excel to Python, with a strong educational background in data science. Aiming to leverage skills and experience to drive data-informed decision-making.

Lead Associate, Data Consulting, Social Lens, Mumbai, India (2022 - 2023)

• Led data management and analysis for a $16 million philanthropic fund, performed data processing, and delivered cross-sectional insights to senior leadership for informed decision-making and strategic course correction.
• Spearheaded technology adoption initiatives in the organization by providing strategic guidance to leadership, offering recommendations on technology investments backed with a cost-benefit analysis to enhance organizational efficiency.
• Created a data repository and performed analytics to understand the time required for each program, provided timeline estimation to the clients, and assisted in resource planning for different programs. 
• Published Tableau dashboard on the company’s website to track the progress of a novel capacity-building initiative.

• Managed the ETL (Extract, Transform, Load) process for a major food and agriculture business company, and consistently delivered 100% resolution rate for client queries on the ETL results, offering prompt ad-hoc solutions. 
• Developed and modified SQL routines to detect fraudulent transactions to safeguard the company from internal fraud.
• Designed and built dashboards to report fraudulent activities while maintaining existing dashboards for accuracy and efficiency, and incorporating changes using Tableau.

• Collaborated with industry experts to develop comprehensive interview guides and templates for data collection, ensuring a holistic capture of relevant information.
• Utilized Python to perform topic modeling and clustering analysis on qualitative data, uncovering common trends within the dataset and aligning findings with theories from relevant journals.

• Conducted comprehensive investigations into warranty expenses incurred by the company, employing advanced analytical techniques to identify root causes and patterns, and recommending appropriate mitigation strategies.
• Implemented measures based on Lean Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) methodology to reduce warranty expenses and improve the repair process, resulting in a significant 54% enhancement.

• Improved time frames by approximately 40% for ongoing data capturing process by developing an automation tool in MS Excel and tuning it to the business process outcomes.
• Pioneered an SQL-like database in Excel to streamline data collection and retrieval to improve the data management processes without the need for new technology, providing a user-friendly solution.

Master of Information Management, Syracuse University (2017 - 2019)

• Certificate of Advanced Studies (CAS) in Data Science
• Excellence Scholarship from the iSchool
• Graduate Mentor