Data Analyst

ANCHAL JAIN

**********@*****.***

214-***-**** https://www.linkedin.com/in/anchaljain29/ https://github.com/anchaljn29/ Education

The University of Texas at Dallas May 2021

M.S. in Management Information System- Business Intelligence and Analytics track 3.65/4.0 Rajiv Gandhi Proudhyogiki Vishwavidyalaya (India) June 2018 B.E. in Computer Science 3.7/4.0

Technical Skills

Certifications: Google Analytics for Beginner, Google Ads Search, Google Ads Display Programming: Python (NumPy SciPy Pandas Scilearn), SAS Programming, R, DAX, HTML, CSS, Database structures Analytical Tools: SQL Server, Tableau, Power BI, Microsoft Excel, Salesforce Admin, Salesforce Sales Cloud Algorithms: Regression, Random Forest, SVM, Decisions tree, Neural networks Work Experience

Fusion Consulting Inc (Healthcare Data Analyst Intern) August 2020 – December 2020

• Helped clients by defining CRM roadmap and evaluating their technology business process.

• Identified and prepared 80+ user stories that saved time when prioritizing the implementation of requirements and functionality.

• Designed and developed Sales cloud to automate the sales process, that helped in increasing productivity by 35%, and sales revenue by 28%.

• Created Reports and dashboards to track sales activity by sales rep, top opportunities, and total closed business. Office of Information Technology (Data Analyst) January 2020 – August 2020

• Performed extensive data cleansing and analyzed the data using pivot tables.

• Formulated Macros function to classify different colors into 4 categories that reduced the time for daily reporting.

• Created bar graph, and histogram to provide an overall report of loaner program to the manager that shows the availability of computers, and laptops.

Projects

Sprocket Central Data Analysis (Power BI)

• Leveraged Power BI to create visually impactful dashboards for data reporting by using DAX, measures, and graphs. Generated 3 different reporting tools for Marketing, Sales and Management.

• Identified 200 top prospective clients, out of 1000 prospects by analyzing current sales trend and customers that are highly likely to purchase the products from the company that increased the revenue by 30%. Global Super store Analysis (SSMS, SQL)

• Operated with the Enterprise Data warehouse team and established Data Architecture to create BI, ETL Standards and Procedures to meet Business Unit's needs.

• Designed ETL data load into data warehouse from various sources using SQL Server/SSIS, performance tuning of ETL jobs & used Power BI for reporting.

• Analyzed Data in Enterprise Data mart to identify the root cause of bugs in end Reports and proposed a fix which reduced the report load time.

Truck fleet data Analytics

• Ingested Truck fleet data into Hadoop ecosystem using Sqoop, Flume and performed data cleaning and transformations using Spark. Created tables in Impala and implementing PIG Script logic for loading data in Impala.

• Integrated Impala with Tableau via Cloudera Hadoop Server, Implementing Linear Regression using R with deployment in Tableau for visualizing driver’s risk factor and calculating threshold to determine risk factor for each truck driver via Rserve.

Mortgage Default Prediction, Supervised Machine Learning (Python)

• Created a Classification data model to predict risk factor for loan default by customers, with best test score of 98%.

• Demonstrated Bias-Variance trade off, performed GridSearchCv to optimize model, cross validated using K-fold.

• Recommended neural network (0.984 AUC) significantly outperformed a basic linear regression model (0.799 AUC), therefore validating the performance benefits of neural network.

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