Namratha Kasineni

Hartford, CT ***** • 248-***-**** • ac5yyp@r.postjobfree.com• https://www.linkedin.com/in/namrathakasineni Data Science • Project Management • Analytics

CAREER OVERVIEW

Over 4 years of professional expertise in unveiling data driven business insights, reporting, consulting and data analysis in Banking & Finance domains with strong background in SQL, R, SAS, Python, Google Analytics & Tableau EDUCATION

M.S. in Business Analytics and Project Management (4.0/4.0) (University of Connecticut) May 2018 Bachelor’s in Information Technology (8.7/10) (SASTRA University) June 2012 EXPERIENCE

Data Science Analyst, Stanley Black & Decker (UCONN) Jan 2018-May 2018

• Performed extensive data pre-processing using Natural Language Processing techniques on internal audit data in R

• Predicted and mapped the fixed assets to specific classes based on the descriptions provided in the firm’s policies by leveraging machine learning techniques like Random Forests, Logistic Regression and Decision Trees

• Transformed business questions into actionable insights through visualization and ensured repeatability and sustainability in code Digital Marketing and Analytics Consultant UGC, Fish Element Nov 2017-Apr 2018

• Planning and maintaining company's social media presence through digital marketing campaigns, email and social media

• Analyzed trends in the data constantly using google analytics to come up with new strategies to boost the sales

• Facilitated optimization of landing pages and strategized to increase the conversion rate and customer acquisition rate Graduate Teaching Assistant, Project Leadership and Communication, UCONN School of Business Sep 2017-Apr 2018

• Collaborated with professor to design comprehensive coursework, challenging questions for assignments and exams to enhance analytical skills and supported in grading case studies Tata Consultancy Services Bengaluru, India

Senior Data Analyst Jan 2015- Dec 2016

• Led a team of 8 and managed various aspects: planning, requirement gathering, estimating, scheduling and actively engaged with SME’s and business leaders to gain insight on applications/firm policies and processes affecting the decisions on the products

• Built Tableau dashboards to track, report and gauge the performance metrics of the team to improve utilization and efficiency

• Acted as a liaison between business & tech teams and also supported User Acceptance testing (UAT) and maintenance handovers Business Data Analyst July2012 – Dec 2014

• Applied strong functional knowledge to draw out data-driven business requirements completely and accurately from stakeholders

• Conducted requirements analysis/engineering based on all possible business scenarios and use cases and developed both functional specification documents and designed captivating charts on a Tableau dashboard

• Partnered with cross-functional business leads to analyze huge data schemas and present the insights/anomalies to leadership team

• Experienced in both Agile and Waterfall platforms in delivering analytical and IT projects throughout the SDLC

• Well versed in developing robust test suite and performing functional, regression, smoke testing on standalone and web applications ACADEMIC PROJECTS

Walkart Customer Analytics

• Applied pre-processing techniques like Feature Engineering, Principal Component Analysis to bring out the innate patterns in data

• Predicted the customized price of the product by analyzing the customer purchase behavior using ML algorithms like Linear Regression, Decision Tree and Clustering in JMP and R and achieved an accuracy of 86% Predicting Employee Attrition

• Worked on the employee survey data of the company to identify the trends in the data through exploratory analysis in R

• Executed Decision Trees and Clustering techniques to predict the association between employee characteristics and attrition

• Provided recommendations based on market research to curb employee attrition and increase employee satisfaction index Sentiment Analysis on Amazon Customer Reviews

• Performed intensive data preprocessing using NLP techniques: Stemming, Tokenization, Stop words removal and Feature Engineering

• Implemented Multinomial Naïve Bayes, Logistic and K-Fold (10) Logistic Regression models in Python

• Explored Ensemble methods and implemented to improve the accuracy of the model from 79% to 83% TECHNICAL SKILLS

• Machine Learning: Hypothesis Testing, ANOVA, Statistical Modeling, Linear, Logistic Regression, Decision Tree, Random Forest, Boosting, KNN, K-means Clustering, Principal Component Analysis, Data Mining, Time series forecasting, NLP, Sentiment Analysis

• Languages and Tools: R, SQL, SAS, Python, Tableau, HP ALM

• Certifications: ISTQB certified

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