Data Analyst

Anisha Balakrishnan Hartford, CT ***** 860-***-**** Email www.linkedin.com/in/anb01

EDUCATION

University of Connecticut School of Business, Hartford, CT Aug 2018 - Dec 2019

Masters of Science in Business Analytics and Project Management GPA: 3.80/4

Coursework: Predictive Analytics, Statistics, Business Process Modeling, Data Mining & Business Intelligence, Web Analytics

Anna University, India Jul 2011 – May 2015

Bachelor of Engineering, Department of Electrical and Electronics GPA: 8.05/10

TECHNICAL SKILLS

Machine Learning

Analytical Technique

Statistical Technique

Management skills/tools

Programming Lang.

Regression-Linear, Logistic

Data integration/ETL

Hypothesis Testing

Project Management

Python, R, SAS

XG Boost, LightGBM

Data Warehouse

Bootstrapping

Risk & Cost Management

PL/SQL, MySQL

Gradient Descent, KNN

Market basket analysis

Bagging/Boosting

Agile/Waterfall

Hive, Pig, Scala

Neural Nets, Naïve Bayes

Text Analytics, PCA

A/B Testing, Sampling

MS Project, MS Office

C, C++, AWS

Clustering, Classification

Google Analytics

Probability distribution

Gantt Chart

Java

EXPERIENCE

Cadenza Innovations, Centre for Advancement of Business Analytics, UConn Jan 2019 – Present

Skills & Tools: SQL Tableau SAS Advanced Excel (Macros, PivotTable, VLOOKUP) Project Risk & Cost Management

•Analyzed electric load fluctuations from NYPA to identify peak load and forecasted load for 2 years using Time-series model

•Devised installation cost model and Energy Storage System profitability model; offset energy costs and calculated payback period for installing battery in commercial buildings using 20+ parameters

Larsen and Toubro Infotech, Data Analyst Python, R, SAS, SQL, SPSS June 2015 - Feb 2018

•Performed Segmentation on ~ 10 Million customers with K-means clustering to target customers in South-Asian market and redefined marketing strategies

•Forecasted Plant Unit Sales using Time-series model across different regions using SAS; projections noted error rates between 5% - 15% based on volatility of market and car-lines

•Utilized machine learning classifiers to predict backorder risk of auto parts, automobiles and motorcycles for B2B system; optimized model for expected profit and improved inventory system service level by 9%

•Scrutinized plant history data stored in Hadoop FS to predict car inspection failures from production line by building Classification models; obtained an accuracy of 81.4% with Random Forest model

•Identified key vehicle features by applying Sentiment Analysis (Natural Language Processing) on customer feedback; gave insights that helped earn $32 million

•Conducted Statistical prediction of cancellation behavior among motor insurance holders using Classification Tree model

•Analyzed auto insurance purchase behavior to find factors that affect customer decision using Decision Tree model

•Proposed, analyzed key business metrics for “Voice of the Customer (VoC)” impacting dealerships across Asia-pacific region; boosted customer engagement and response by 30%

•Designed interactive Tableau Dashboards to track KPIs and analyze trends, collaborated with VPs to monitor metrics efficiently and minimized time to skim reports; garnered appreciation from higher management

•Set up an ETL process to obtain, clean, organize data; handled large database and executed optimized SQL queries

•Structured complex SQL queries to generate reports for ad-hoc business requests and automated report generation

ACADEMIC PROJECTS

Santander Value Prediction Data Challenge R, SAS JMP Pro, Tableau

•Compared Linear Regression, Decision Trees, Random Forest, Support Vector Machine models; Gradient boosting model predicted value of transactions for each potential customer with AUC 0.711

Voya Email Data Challenge Python (Scikit-learn), Tableau, MS PowerPoint

•Proposed ideas to accelerate customer engagement and boost potential business using Text Mining techniques

•Implemented bag of words model; determined sweet spot and gave recommendations to improve click through rate

Expedia Hotel Group Recommender System Python (NumPy, Pandas, Scikit-learn), Tableau

Contextualized millions of rows of buyer data to predict the likelihood of a user to stay at 100 different hotel groups

Created an algorithm to generate user probability of staying at each hotel group and predicted top 5 most probable clusters

Movie Review Sentiment Analysis Python (TensorFlow, TF-IDF, NLTK, matplotlib), R

• Assigned sentiment labels for movie reviews scrapped from Rotten Tomatoes

• Used techniques like bag of words, Tokenization, Lemmatization and built Neural network models using keras

Automated Employee Leave Management System; generated reports using Oracle SQL (DML & DDL statements) and Visio

LEADERSHIP AND ACCOMPLISHMENTS

•Orchestrated events, prepared budgets, secured and allocated funds as VP Finance, Graduate Finance Association UConn

•Received Pat-on-the-back award for saving a cost of 19000 USD to company by streamlining a business process

•Maintained highest client satisfactory index of 4.92/5 in a team having more than 42 members in LTI

•Spearheaded and trained a team of 4 members, delivered project 12 days before deadline with estimated $32,000 savings

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