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Data Analyst Python

Phoenix, AZ
May 17, 2020

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Nitin Rana

**** ******* ******,********** *****,CA,92647 313-***-**** LinkedIn Analytics professional with 4 years of practical experience in data analytics, generating insights, storytelling, automating, developing and compiling reports and dashboards. Proficient in Statistics, ML, Statistical Modeling, R, Python, SQL EDUCATION

University of Connecticut - M.S. in Business Analytics and Project Management (GPA 3.78/4.0) Jan 2019-May 2020 Coursework: Statistics, SQL, Predictive Modeling, Python, Data Visualization, Business Intelligence, Big Data with Hadoop Maharishi Dayanand University - Bachelor of Technology in Electronics and Communication Aug 2008-May 2012 PROFESSIONAL EXPERIENCE

UConn Graduate Consulting Group Data Analyst Consultant Hartford, CT USA Feb 2019-Feb 2020 LIMRA Python, SQL, Tableau

• Analyzed 2M+ records at policy, agent level and predicted the factors driving Insurance product profitability and proposed new metric for policy agent profit index calculation

• Identified factors affecting policy churn and designed tableau interactive dashboards that helped marketing team optimize the pricing strategy

Blue Earth Compost Google Analytics, Power BI

• Monitored website traffic using Google Analytics and determined KPI’s to measure A/B test result to increase viewership on website, helping business gain viewers by 30%

• Analyzed KPI’s using dashboard and provided actionable recommendations to marketing team; increasing customer subscription by 10%

Tata Consultancy Services Data Analyst Gurgaon, India Jan 2015-Jan 2019 Churn Analytics Python, Tableau, SQL

• Engaged with stakeholders to capture business requirements and develop prudent analytical solutions

• Effectively cleaned data using python by imputing missing values, treating outliers, using dimensionality reduction etc.

• Collaborated with data scientists to build ensemble tree models for churn prediction and life time value (CLTV) calculation; increased retention rate by 10%

• Created interactive Tableau dashboards for tracking client KPI’s, providing higher management one stop dashboard to track over 16 metrics

• Managed projects following Agile-Scrum methodology and handled sprint planning, daily scrum and backlogs Customer Segmentation & Re-engagement Python, Tableau, Informatica

• Identified cross selling and up selling opportunities by customer segmentation for various company products using k-mean clustering saved marketing cost by 8%

• Extensively created scripts to ingest large amount of customer data from multiple sources through ETL pipelines

• Worked with business analyst to design dynamic dashboard, using Tableau and SQL thereby saving 10 man-hours/week

• Led and mentored team of 6 in exploratory data analysis, descriptive analytics and predictive analytics helping them ramp up fast in technical and business knowhows

Ad Hoc Reporting and Data Analysis SQL, Excel, Tableau

• Aggregated data from raw and disparate sources to construct streamlined data pipelines using highly optimized SQL queries

• Provided analytical and data support to engineering teams for setting up data repository and transforming unstructured data using SQL and Excel

• Created a data acquisition and quality framework which acted as a standard for multiple teams saving 162-man hours/yr

• Automated metrics to track daily status of various teams through Tableau-based dashboard, reduced manual work by 60%

• Leveraged Excel for Ad Hoc analysis to create Monthly Operational Reports (MORs) using pivot tables and macros TECHNICAL SKILLS

Machine Learning: Generalized Linear Models, Decision Tree, Random Forest, Boosting, KNN, Naive Bayes, SVM, PCA, Clustering, Time Series models, Neural Networks, NLP, Validation techniques, Market Basket Analysis, Variable Transformation Statistical Analysis: Hypothesis Testing, A/B Testing, Data Cleaning, Data Mining, ANOVA, Quantitative Analysis Data Analysis: Exploratory Data Analysis, Feature Engineering and selection, Text Mining, Customer Analytics Tools: Tableau, Python (NumPy, Pandas, Skicit-Learn, Matplotlib), SQL, Informatica, Linux, MS Excel, SAS Enterprise Miner, MS PowerPoint, MS Word, MS Visio, SAS JMP, Pentaho, SSRS, SSMS, Hadoop, Big Data, TFS, Hive, Pig, Spark, AWS, Google Analytics ACADEMIC PROJECT

Travelers, Insurance Claims Fraud Analytics Python, R, Tableau

• Identified first-party physical damage fraudulence explaining reasons of fraudulent claims based on historical data. GBM model with 10% misclassification rate

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