"A senior analyst with a specialty in fraud detection and customer segmentation in the finance industry for three-years. Looking for opportunities to leverage my skills in Python, SQL, and SAS in the predictive analytics domain to improve customer experience and mitigate risk"
University of Southern California, Marshall School of Business - Los Angeles, CA 08/2019 - 12/2020
Master of Science in Analytics (STEM), Dept. of Data Sciences and Operations
Courses: SQL for Database, Data Driven Statistics, Data Wrangling (Python), Machine Learning, Prescriptive Analytics using Optimization Techniques, Business Analytics, Marketing and Fraud Analytics, NoSQL Databases in Big Data, Text Analytics and NLP, Tableau
Leadership: Teaching Assistant: Applied Business Statistics and Senior Thesis, World Business Bachelors Senior Thesis
Indira Gandhi Delhi Technical University for Women - New Delhi, India 08/2012 - 05/2016
Bachelor of Technology (B. Tech), Electronics and Computer Engineering
Management Summer Internship: Hong Kong University of Science & Technology
Barclays PLC – India
Senior Quantitative Analyst 04/2017 – 05/2019
Developed beneficiary fraud model for New-to-Bank USA customers using classification modelling by applying predictive analytics to identify application fraud and performed missing value treatment, variable selection, and segmentation analysis to prevent bank from reputational damage by capturing 23% of fraudulent accounts.
Designed a streamlined dashboard using SAS and MS-Excel to monitor quarterly performance of risk models based on accuracy, efficiency, stability and sensitivity; reduced run-time by 40% and decreased 75% manual labor utilization; awarded Barclays Recognition Award for Excellence for the outstanding performance
Led segmentation of credit card customers using K-means to exclude high risk customers from getting a credit limit increase for Mastercard and Visa portfolio: resulting in 37% drop in fraud amount and $374K overall profit for Barclays
Extracted data using SQL to feed in Logistic regression machine learning model for predicting the riskiness for newly acquired customers of Barclaycard USA using FICO score; identified ~8% fraud cases
Headed Data Governance to audit KPI metrics reported to stakeholders and modify strategies in subsequent quarter based on continuous engagement with teams in USA and UK to streamline Impairment, Capital, and Behavioral models (Application scorecard and Fraud)
Risk Analyst 07/2016 – 03/2017
Successfully implemented customer profiling using SAS and Tableau to target Mauritius customers for cross-sell and up-sell banking products; driving engaged index by 32% and incremented customer spending by 10% in consecutive quarter.
Performed gap analysis to investigate risk reporting and designed a framework to make the processes BCBS239 compliant
Developed acquisitions data mart and reconciled risk reporting, reducing six reports to one streamlined process with higher accuracy
ACADEMIC DATA SCIENCE PROJECT 08/2019 - 01/2020
Unsupervised Machine Learning Fraud Model on New York Properties Data using Python
Generated expert variables followed by z-scaling them; performed Principal Component Analysis for dimensionality reduction
Applied Quantile Binning to compute fraud score calculated by Euclidean distance and auto-encoder of z-scored PCA values
Exploratory Data Analysis for Centro using Linear Regression
Executed data manipulation using Python on the rental and sales real estate dataset for quantitative analysis of investment in USA market
Utilized feature engineering and applied Linear regression to estimate rental income and accurate sales price as output
Designed an evaluation tool using MS Excel to estimate correct profitable margin using KPIs of a real estate property
ENTREPRENEURIAL EXPERIENCE 03/2014 – 05/2015
Partee Hai – India
Founder & Chief Marketing Officer
Founded, developed and launched “Partee Hai”, a mobile application with a team of ten developers and interns
Spearheaded business growth in three Indian cities by conducting market research and allocating resources; on-boarded 200+ merchants within six months of product launch and maintained 20% monthly growth in client’s acquisition.
Managed social media marketing strategies by constructing campaigns and collaborating with design studios; increased social media followers by 30% month-over-month and customer engagements by 625% in six months.
Languages: Python (Pandas, NumPy, Sckit learn, TensorFlow), SAS, SQL, NoSQL (MongoDB, Neo4j), R
Visualization: Power BI, Tableau, Python: matplotlib, seaborn
Modeling: Machine Learning Algorithms: Linear Regression, Logistic Regression, Decision Trees, Random Forests, KNN, K-means,
Principal Component Analysis (PCA), XGBoost, Partial Least Squares Regression (PLSR)
Statistics: Hypothesis Testing (e.g. A/B tests), ANOVA, Chi Square Test, T-test, F-test
Data Tools: RStudio, SQL (PostgreSQL), Python (Jupyter), MS Excel, Google Analytics, Tableau, Dashboarding
Certification: Risk Passport Holder by Institute of Risk Management, Barclays Lean certificate by Cardiff University
Area of Interest: Predictive Analytics, Visualization, Product Management, Data Strategy, Data analysis, Data Mining