Shivani Singh

ad1jho@r.postjobfree.com 857-***-**** NewYork LinkedIn GitHub

EDUCATION

Columbia University, New York, NY MS-Applied Analytics Sep 2023 - Dec 2024 Relevant coursework: Strategies in Organizational Context, Financial analysis, Machine learning, Data analysis and visualization Goa Institute of Management, Goa, India MBA May 2019 - Jun 2021 Relevant Coursework: Statistics, Strategic Management, Storytelling Using Data, Project management, Marketing and retail analytics BBD NITM, UPTU, Lucknow, India B.Tech, Computer Science Mar 2013 - Apr 2017 Relevant Coursework: Data Structures, Software Project Management, Design and analysis of Algorithms, Software engineering, Machine Learning SKILLS

Programming Languages and software tools - Python (NumPy,Pandas, SciPy, scikit-learn, TensorFlow), R, SQL (advanced data analysis), MySQL, PySpark, - PowerBI, Tableau, Excel, AWS, Git, Jira, Hadoop, Natural Language Processing Core Skills - Stakeholder management, modeling, Go-to-market startegy, Team management, Reporting, RFP Proposals and client presentations WORK EXPERIENCE

Virtusa, Bangalore, India Senior Consultant at Analytics and AI Division Jun 2021 - Jul 2023

• Optimized clinical trial audit process: Used Amazon Comprehend automation, achieving >88% accuracy in sentiment analysis, leading to a 40% reduction in audit review time, boosting decision-making efficiency – project link

• Achieved $1.25M/Year Cost Reduction in employee man-hours, by employing advanced statistical and machine learning methods to develop a smart anomaly detection system to detect irregularities in audit trails in clinical trial data for a major pharmaceutical client

• Liaised closely with Senior VP to do budgeting analysis for projects to be taken up, resource and effort-based cost analysis and resource allocation across Fintech Solution Development and Health Sciences Solution development teams within firm

• Drove $3M Revenue Increase: Conducted in-depth revenue analysis, crafting interactive Tableau and Excel visualizations, facilitating a revenue boost in North America and EMEA analytics track

• Delivered 70% Conversions (Q1 & Q2 2023): Spearheaded RFP research and development on ML use case presentations to prospective businesses on decision trees, multi-label classification, regression analysis and neural networks Virtusa, Hyderabad Management Intern Apr 2020 - Sept 2020

• Devised Personalized Financial Recommender System: Engineered features viz. customer profiles and transaction history, resulting in a 25% increase in customer product engagement and a 30% boost in cross-selling for an American IBAB bank

• Employed machine learning to forecast user stress levels and predict potential heart stroke risks from wearables, resulting in a 20% improvement in stress level accuracy and early detection of high-risk cases for health insurance clients HCL Technologies, Noida, India Software Analyst May 2017 - Jun 2019

• Accomplished 30% cost reduction by creating dashboards for inventory planning and procurement forecasts. Optimized Software Asset Management and procurement costs for a Fortune 500 client

• Tracked Revenue Analysis by creating interactive dashboards and reports on Tableau and MS Excel

• Boosted Retail Profits: Developed a robust customer segmentation model utilizing 11-year store data, employing K-means clustering and Decision Tree algorithms, resulting in a 25% increase in high-value customer targeting efficiency for the retail client PROJECTS

Recommender System for Bank Products (FinTech Industry) April 2020 - July 2020

• Objective: Developed a Recommender System examining 45+ user variables, increasing customer experience and increasing cross-selling effectiveness

• Methodology: Combined Content-Based and Collaborative Filtering techniques to analyze user preferences based on both individual product features and collective user behavior, enhancing recommendation accuracy

• Results: Utilized KNN Classifier to process extensive user-item interactions, attaining 78-85% accuracy rate through meticulous hyperparameter tuning and algorithm optimization in a hybrid filtering framework Natural Language Processing (NLP) Sentiment Analysis Engine (Retail Industry) April 2020 - May 2020

• Objective: Implemented Natural Language Processing (NLP) techniques on 15 years of customer reviews data, deriving actionable insights to optimize marketing strategies and enhance customer satisfaction

• Methodology: Processed and analyzed a vast dataset comprising 668,454 reviews spanning 15 years, involving 377,059 users and 87,658 products; Applied techniques including text preprocessing, stemming, and vectorization (utilizing Bag of Words and TF-IDF) to extract sentiments comprehensively from textual data

• Results: Analyzed user behavior, identifying influential reviewers and trends in helpfulness, enhancing customer engagement strategies. Achieved 92% prediction accuracy

AWARDS AND RECOGNITIONS

• Selected in top 10% from 150,000 applicants for prestigious Indian Academy of Sciences' Summer Research Fellowship. Contributed to development of India's first microprocessor (Shakti) at IIT Madras, funded by Govt. of India

• Received "HLS Titans Award 22" as a certificate of appreciation for contribution in Client's saving $1.25M/year (June 2019,HCL)

• Secured 1st runner-up in SAS Hackathon - National Data Analytics Championship, competing against 300+ teams in India (April 2020,GIM)

• Winner of National Hackathon, out of 470 participating business schools, by predicting direction of top 10 stocks in the U.S. market.(May 2021,GIM)

• GRE Overall score : 339/340 - 170/170 in Quant (99th percentile), 169/170 in Verbal Reasoning (96th percentile)