Data Analyst

ASHMIKA SHRUNGARPURE

Phone: +1-682-***-**** ************.*******@*****.*** https://www.linkedin.com/in/ashmika-shrungarpure/ Career Summary

I am looking forward to make a big difference as a Data Analyst /Data Scientist utilizing my skills,experience, and passion for my profession. I have proficient knowledge in mathematics, statistical analysis, regression analysis, and data analytics used for business operations. I am also well-versed with data collection, cleaning and data visualization, and have strong analytical and interpretation skills. Expertise in SPSS, Advanced Microsoft excel, tableau, SAS, SQL, cloud computing, Data Science using machine learning, Trend Analysis and Big data. Career Highlights

• Identified dealer opportunities worth millions of dollars.

• Extracted data insights and presented the data story to the business leader.

• Reduced the vendor dependency and saved the cost of development. Education

Masters in Management Information Systems, University of Texas at Arlington Pursuing Bachelor of Technology, in Computer Science engineering, GITAM University, India May 2016 Skills

Programming and Tools: JAVA, C, C++, SQL, SAP, SAS, R, Seismic, Spyder, Hadoop, Alteryx, python Expertise: Data mining, Business Statistics, Database Management, SQL, Excel, Web Analytics, Economics, data analysis, interpretation, data cleaning, data visualization, data storytelling, Tableau, SPSS. Projects

BUSINESS INTELLIGENCE ANALYST INTERN AT COX AUTOMOTIVE INC (2018)

• Used machine learning techniques in python to perform predictive analysis in estimating the vehicle sales for several car dealerships in the United States. The estimates were a core input in a large project for segmentation of every customer and gave business insights in the Cox Automotive Universe

• Created a seismic playbook by coordinating across the team and managing a strict timeline.

• Analyzed the backend of a software and documented the SQL queries to reduce vendor dependency of the team.

• Gathered requirements through communication across departments to build an integrated database for data integrity.

• Identified dealer opportunity and presented the data story to business leaders. GENRE RECOGNITION THROUGH MOVIE POSTERS (2017)

• Preprocessed the dataset by removing the duplicates, resizing the images

• Converted the images into the numpy array and divided the dataset into train and test

• Used keras to build the model and applied different activation functions AMAZON CUSTOMER REVEIWS (2017)

• Segregated the reviews according to the ratings

• Extracted the branded keyword from the reviews through using keyword extraction

• Suggested the branded keywords which facilitated the increase of sales and customer engagement by 3% SENTIMENT ANALYSIS (2017)

• Collected tweet using python programming regarding the NFL controversy from different data sources

• Examined the tweets using tableau and performed sentiment analysis using the textblob

• Used the same tweets to execute the topic modelling

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