Data Analyst Sales

DEEPANSHU MAHAJAN

Tampa, FL – Available to relocate, Willing to travel 813-***-**** adbfre@r.postjobfree.com LinkedIn SUMMARY

A solution-oriented data analyst with 4 years of relevant experience in analyzing data, building predictive models and developing dynamic business strategies. Skilled in business intelligence and visualization techniques to provide actionable insights. EDUCATION

MS in Business Analytics and Information Systems, University of South Florida Aug 2018 – Dec 2019 Bachelor of Electrical Engineering, Jabalpur Engineering College Aug 2011 – May2015 PROFESSIONAL EXPERIENCE

AutoNation Inc., Fort Lauderdale, FL Jul 2019 – Aug 2019 Data Analyst Intern (Domain: E-Commerce, Sales, Automotive)

Extracted large data set using AWS Athena service with complex SQL queries.

Performed descriptive and exploratory in-depth statistical and inferential analysis to recommend actions to solve customer retention problems.

Developed dashboards using Tableau to track different KPIs to help develop business strategy.

As a part of process improvement, studied overall data flow, identified deficiencies in the existing data collection process.

Worked closely with business and technology leaders to understand the data, business requirements and deliverables.

Identified data entry flaws such as duplication and data degradation to improve data quality. Infosys Technologies, Bangalore, India Oct 2015 – Jan 2018 Systems Engineer (Domain: Healthcare, pharmaceutical Client: Pfizer)

Extracted large amounts of data using advanced SQL queries to generate reports as per given problem statement.

Performed data cleaning using Python to convert unstructured data into structured data for further analysis.

Identified and defined key metrics and performance indicators to drive and strategize business decisions.

Derived intricate insights and presented actionable findings to leadership board using Tableau Dashboards.

Developed a utility based on Java and SQL to deal with redundant information, which resolved 20% of production issues.

Coordinated with cross-functional teams for bug fixing and developing feature upgrades of Java-based web applications.

Documented 50+ Standard operational procedures (SOP) for excessive priority application problems.

Conducted knowledge transfer and brown bag sessions to new onboard on using the client’s applications. SKILLS

Software development methodology: Agile, waterfall.

Languages: R, Python (Numpy, Pandas, Matplotlib, Seaborn, Scikit-Learn), PL/SQL.

Databases: Microsoft SQL Server, MySQL, Oracle database, MS Access.

Visualization/Reporting: Tableau, Power BI, QlikView, SSRS.

Tools: R Studio, Jupyter, Azure ML Studio, SQL Developer, Toad, Spyder, Microsoft office.

AWS: EC2, S3, VPC, Redshift, Athena.

CERTIFICATIONS

Managing Big Data with MySQL, Data Science in R Programming, Inferential Statistics, Business Analytics with Excel, Google Analytics for Beginners, Advanced Google Analytics. ACADEMIC PROJECTS

HR Analytics – Data Modelling Project (R and Power BI) Aug 2018 – Dec 2018

Analyzed the IBM Watson Data to perceive elements affecting the job satisfaction of employees.

Built an ordinal logistic model in R and compared the various evaluation metrics of models for the best prediction. JetRail Traffic Prediction – Time Series Project (Python, Tableau) Jan 2019 – May 2019

Forecasted the traffic of JetRail for next 7 months to help them to make better decision for investment in Python.

Used time series techniques for forecasting the traffic. Sales Prediction – Machine Learning Project (R, Tableau, Excel) Jan 2018 – Apr 2018

Predicted sales of 1559 products across 10 stores by ran Regression (Lasso and Ridge), Random Forest, and XGBoost with 10-fold cross-validation technique to test model performance based on RMSE.

Determined the attributes that play a key role in increasing overall sales. USA Crime Analysis – Data Visualization Project (Tableau, Excel) May 2018 – Jul 2018

Successfully analyzed and visualized US Crime records using Tableau.

Determined most and least committed crimes and identified areas with the highest and lowest crime rate.

Determined the correlations among crime, age, gender, and race by regression and plots.

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