Decision Science Consultant

Prachi Gupta **************@*****.*** • 201-***-**** • Menlo Park, CA 94025 • Linkedin

EDUCATION

University of Connecticut: GPA 4.0/4.0 - MS in Business Analytics and Project Management JAN 2017 - AUG 2018 Guru Gobind Singh Indraprastha University, India - Bachelors in Electronics and Communication AUG 2006 - JUN 2010 SKILLS AND CERTIFICATIONS

Algorithms: - Regression, Support Vector Machines, Decision Tree, Random Forest, Boosting, PCA, K-Mean, Hierarchical, KNN, Naïve Bayes, ARIMA, Recommendation System, Hypothesis Testing, ANOVA, Sentiment Analysis, Market Basket Analysis, Neural Network Tools: - Python (Scripting, Pandas, NumPy, SciPy), Java, J2EE, SQL, R, Spark, Hive, SAS (JMP), Tableau, Hadoop, Android WORK EXPERIENCE

LATENTVIEW ANALYTICS, MENLO PARK, CA, Consultant – Decision Science OCT 2018 – PRESENT CLIENT: FACEBOOK

• Collaborated closely with the marketing and research team to understand product scope and market requirements

• Identified target customers for new product launches by building machine learning prediction models (Regression, SVM, Decision Tree, Random Forest, Gradient Boosting) on different demographics and behavioral pattern

• Identified key drivers of customer click and purchase behavior by using models such as logistic regression and decision tree

• Developed experiment design to measure campaign effectiveness by evaluating survey results on test and holdout group

• Developed data pipeline by leveraging structured and unstructured data from multiple data sources in Presto and HDFS SAMSUNG R&D, INDIA, Engineer – Machine Learning MAY 2013 - DEC 2015

Designed scalable machine learning models which adapted to different business needs and product life cycles

Identified critical pain points of customers through cleaning and extraction of issue root causes from customer feedback and comments using Natural Language Processing (Topic Modeling / TF -IDF) and categorized them using Naïve-Bayes classification method with 66% accuracy

Developed customer segmentation of B2B clients using clustering algorithms like DB Scan and KNN to create targeting advertisement and marketing campaign; helped increase customer response rate by 20%

Developed hybrid recommendation system using content and collaborative filtering to find similar applications

Studied the behavior of purchase patterns across phone categories and built a model to forecast the sales

Performed data integration, outlier analysis, missing value treatment, correlation analysis, PCA as part of data preparation

Analyzed key revenue drivers and marketplace performance to advise marketing teams

Maximized KPIs through consumer insights by A/B testing, market basket analysis & churn prediction analysis

Conducted exploratory data analysis to understand ecosystems, user behaviors, and long-term sales trends INFOSYS, INDIA, Engineer - Data Analysis JUL 2010 - APR 2013

Extracted, transformed and analyzed datasets related to customer clickstream to provide insights to clients

Analyzed customer clickstream data to study customer journey funnel analysis and to identify dropout rates for a US based insurance client’s website using SQL; Recommended solution led to 30% increase in customer conversions

Implemented A/B testing on client web page to assess improvement in customer engagement and member conversion ROMP N ROLL, Analytics Graduate Consultant AUG 2017 - DEC 2017

Built project charter and designed the project plan with the layout of RACI matrix highlighting actual business deliverables

Used Recency-Frequency-Monetary value-based segmentation to enhance marketing and retention strategy

Conceptualized marketing campaign for increasing customer engagement and retention using principles of gamification

Used survival analysis to find customer life time value and developed new pricing model to maximize revenue

Developed a customer churn prediction model using Random Forest and Gradient Boosting with 85% accuracy

Developed KPI tracker framework using Tableau to reflect the trends of sales, revenue, top performing products

Built a revenue forecasting machine learning model to predict the customer equity which helped in formulating price ANALYTICS PROJECTS

Credit Default Prediction (SAS JMP): Github - Developed a new algorithm for filling the missing values in the data. Deployed dimensionality reduction techniques (PCA) and developed model with 80% accuracy. Gender Prediction (Python) : Github - Developed a supervised machine learning model to predict the gender of a person with variables like username, status and description. Used NLP to extract features from the description. Accuracy of the model was 80% Geospatial data analysis (R Studio, Tableau): Github, Tableau - Performed geo-spatial analysis on large dataset of NYC Yellow Taxi and Citi bike trips; Analyzed impact of nearest Citi bike stations on Yellow Taxi trips using KNN algorithm and cluster analysis

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