Mental Health Data

Aparna Gopakumar

**************@*****.*** (203-**-***** https://www.linkedin.com/in/aparna-gopakumar/

PROFESSIONAL EXPERIENCE

PRICELINE.COM

Data science Intern, Customer Retention Analytics (Aug 2019-Dec 2019)

●Developed an optimized relational database in SQL in snowflake schema to restructure the raw aggregate records to a usable form.

●Preprocessed, performed data wrangling and feature engineering using Python data manipulation libraries pandas, numpy, and scikit learn.

●Performed cohort analysis, developed machine learning models (Decision tree, logistic regression, support vector machines, random forest) to predict the probability of repeat engagement of customers

●Presented actionable insights from the data analysis on customer booking behaviors using Tableau dashboards to stakeholders. Identified key customer segments and formulated recommendations supported by statistical analysis.

●Collaborated with 2 Marketing interns and drove experimentations and competitor analysis and developed a KPI to measure the deal experience of a new visitor. Increased retention by 30%.

●Built a customer lifetime value model (buy till you die probabilistic model) using Python lifetimes packages to predict the customer lifetime value of a customer

●Proposed an A/B testing strategy to improve the recommendation system based on location of the user to CMO of Priceline. Earned Best presenter award among 8 intern presentations.

TATA CONSULTANCY SERVICES (Business: GE Healthcare)

Data Engineer, Salesforce, Apttus CPQ Customization (Oct 2015- Nov 2018)

●Developed data models to streamline the business process. Developed algorithms in SQL for automatic extraction of records.

●Developed triggers to manage Oracle database events saving 90 minutes of manual extraction of records.

●Designed workflow rules to develop automated email systems to control the data security issues.

●Optimized the production level SQL code and reduced the processing time of the pricing system by 56 seconds. Earned Lean Six Sigma Green Belt for process optimization.

●Implemented Salesforce BI analytics dashboards and reports to analyze the data quality. Presented to senior business stakeholders of GE. Earned Star performer of the year among 120 associates.

Salesforce Developer, (Business: Thomson Reuters)

●Developed complex algorithms in Java (salesforce Apex) to automate quote to cash functionality, driving business $1.51 billion incremental revenue while reducing manual interference by 18%

●Productionized a total of 58 user stories, leading a team of 12 developers in the development of EU region specific business. Earned Agile Practitioner Certification.

UCONN School of Business

Teaching assistant, Statistics in R (Aug 2019-Dec 2019)

●Assisted to teach 60 student statistics in Business analytics using R. Conducted separate classroom sessions to help students clear the concepts of statistics

EDUCATION (Beta Gamma Sigma Member)

●University of Connecticut MS in Business analytics (May 2020) (GPA: 4.18)

●University of Calicut, India Bachelors in Computer Engineering (May 2015) (GPA: 3.8)

relevant coursework: Predictive modeling, Database management, Time series analysis, Natural language processing, Deep learning, Applied statistics, Visual analytics using Tableau, Big data using Hadoop

RELEVANT ACADEMIC PROJECTS (https://github.com/aparnagkumar)

●Defense marketing for Potoo Solutions: Developed a machine learning algorithm (Softmax Neural network) to help Potoo identify the distribution leak of their clients in Amazon platform. (SQL, Python)

●Data exploratory analysis of BRFSS 2013 data- Analyzed BRFSS survey text data using visualization libraries of R to analyze the impact of education on the lifestyle and awareness of mental health.

●Amazon fine food review –Performed a sentiment analysis of amazon fine food reviews, in Python, using NLP algorithms BOW, TFIDF and Word2vec.

●Music generation using deep learning: Developed a Char-RNN algorithm using deep learning libraries of python (PyTorch, Tenserflow and Keras) to generate personalized music recommendations.

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