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Vidush Bhardwaj

Data Analyst

About Candidate

Education

M
Masters in Data Science 2024
University at Buffalo
B
Bachelors in Mechanical Engineering 2019
Dehradun Institute of Technology

Work & Experience

F
Fraud Analyst 08-05-2019 - 09-30-2021
Wipro Technologies

• Managed end-to-end financial crime transaction process from creating rule engine to advance analytics using AWS
Redshift to streamline data integration and processing
• Employed rule-based fraud alerts on internal transactions, securing nearly 56% accuracy
• Utilized SQL and Python for fraud pattern identification, achieving approximately 75% accuracy and employed Jenkins
for ETL data preparation
• Worked with a team of high-performing data science professionals, and cross-functional teams to identify business
opportunities and build scalable data solutions using google analytics tool (GA4)
• Mentored a team of 4+ members in diverse data analysis methodologies, empowering them to develop robust analytical
skills and contribute effectively to our projects
• Led AB test executions and user application sessions while productionizing the application

D
Data Analyst 04-01-2022 - 07-31-2022
DISYS India Pvt. Ltd.

• Elicited and documented business requirements by contributing to effective collaboration and solution development
across finance department and stakeholders
• Introduced data analytics framework, boosting profits by 14.7% through increased hiring efficiency
• Streamlined processes and computed key performance indicators to analyze recruitment data using Python and SQL,
reducing time to fill roles by 12.5% and enhancing candidate quality
• Directed team in Tableau dashboard development, strategizing to cut hiring costs by 18% and enhance candidate
engagement and retention by 22%

D
Data Scientist 01-01-2024 - 05-15-2024
Lehigh Valley Justice Institute

• Generated regular and ad hoc reports while collaborating with stakeholders to gather project requirements
• Crafted a regression analysis dashboard in Tableau to assess Pennsylvania's incarceration rate changes alongside
mental health spending and education census data while preprocessing data using Python
• Aiming to provide recommendations for policy adjustments with the objective of achieving an 18% reduction in
incarceration rates