Data Analyst Python

SRAAVYA PATHSAMATLA *******.*@*****.*** 773-***-**** GitHub Tableau LinkedIn

Data Analyst with 4 years of experience in building predictive models. As a masters graduate in business analytics, I work closely with SQL, R, Python and Tableau in implementing various data mining and visualization techniques. My goal is to be a data science and analytics expert by collaborating with people and delivering the best business solutions. Academic Qualifications

Master’s in Business Analytics, University of Illinois at Chicago Jan - Dec 2019 Teaching Assistant President – Business Analytics Organisation CGPA – 4 Master’s in Business Administration, Indian Institute of Management, Kozhikode Jun 2014 - Apr 2016 Awarded merit scholarship for scoring amongst top 5% students in the batch Bachelors in Electronics & Communication Engineering – The LNM IIT, Jaipur Aug 2010 - May 2014 Received Chairman’s Gold Medal –Excellence in academics, sports and cultural activities Skill Set

Certifications Tableau Certified Associate AWS Certified Cloud Practitioner IBM BPM Certified Programming Skills SQL R Python RapidMiner Tableau Spark Hadoop MapReduce BPM RPA QTP Processes Project Management Agile and Waterfall SDLC Process Improvement Cloud Capabilities Statistical

Methods/Technologies

Statistics Hypothesis Testing Data Mining Text Mining Predictive Modelling Demand Forecasting Time Series Analysis Regression Models Data Architecture Machine Learning Data Visualization Big Data Automation Business Design Segmentation Analysis Work Experience (4 years)

Data Analyst - CUNA Mutual Group, Madison Jan 2020 - Present

• Developed analytical solutions to meet business requirements and monitored full life cycle of task implementation

• Developed models for automation of claims by data ingestion, cleaning and storing to SQL databases using Python

• Created migration and implementation plans, test models, scripts for data warehouse unit and integration testing Claim Prediction Analysis:

o Forecasted upcoming customer claims and developed pricing models to predict optimal premiums using SVM o Developed modelling algorithms in Python to prepare individual customer portfolio by detecting relations between claims and causal factors, implementing high dimensionality and detecting the missing observations Semantic Analysis:

o Preprocessed data from customer emails, classified POS after stemming process and applied machine learning techniques to output user sentiments, requests and classify them according to the products o Developed an automated due date generation and task notification model based on the extracted key words Fraud Claim Detection:

o Extracted XML data from Hadoop and preprocessed it to use k means clustering algorithm to find anomalies in fraud detection and save the predictions to DB2 database o Built in-house analytics dashboard to stage-wise validate claim data and achieved 95% classification accuracy Data Science Intern - Rewards Network, Chicago Aug - Dec 2019

• Predicting rate and duration of customer churn and analysing various factors driving churn using LSTM – RNN model

• Reduced third party reporting costs by $100K p.a. and automated sales forecasting through Neural Network models Data Analyst - UI Health, Chicago Jan - Dec 2019

• Visualized PCP data for 28 clinics using Tableau and reported key metrics that boost operational efficiency by 13.6%

• Assessed the completeness and validity of patient health records and other data sources. Cleaned 40% of the data Senior Data Analyst – Pidilite Industries, Chennai June 2016 - Dec 2018

• Studied customer portfolio, behaviour and insights to assess new opportunities and maintained contacted network of 600 service national level providers to work in collaboration as a team and promote data-driven decision making

• Analyzed digital data sets and aggregated results to develop hypotheses for A/B tests and orderly implement them

• Designed recommender systems in Python and generated promotional forecasts of products with accuracy of 83.4%

• Developed automated scripts in SQL to generate JSON files to upload data into google cloud from PostgreSQL tables

• Interfaced with Sales, Customer Service and Finance to understand business performance and drive scrum process to implement policies and procedures related to product development, launch, supply chain and marketing actions

• Used Google Analytics-Google Tag Manager to improve online product views and increase customer loyalty by 24% Academic Projects

Uber sentimental analysis of customer reviews Python, SQL

• Performed sentimental analysis of customer reviews to predict a score and projected insights on arrival delays, wait time, number of rides per driver and number of trips logged in by an average individual to launch a new app feature

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