Data Analyst Software Developer

Saumil Shah

Ph: 617-***-**** Email: *************@*****.*** LinkedIn: /in/saumilshah4/

Summary

Engineer with four years of experience in Data Engineering, Analysis, Visualization, Warehousing, Mining and Business Intelligence. I have led and spearheaded changes that improved analytical operations and ETL pipelines. Identified appropriate solutions while working in agile development teams contributing to success of organization and helped businesses leaders with insights to make better decisions. I am hoping to leverage my knowledge and experience to provide leaders in the organization key actionable insights for data driven decision making. Technical Knowledge

Programming Languages: R, Python, Java

Databases:

ML Libraries:

Tools:

Postgres, MSSQL, Oracle, Cassandra, AWS Athena, MySQL, MongoDB Scikit-learn, NumPy, pandas, PyTorch, Keras, NLTK, BeautifulSoup, Flask, boto3 Jupyter Notebook, Tableau, Power BI, Docker, Dask, Talend, Alteryx, Git, Jira, Microsoft Excel, Google Sheets, Toad Data Modeler

Professional Experience

Luna Care, California, USA May 2020 - Present

Data Analyst

• Handled problem solving with data cleaning, data validation and developing interactive dashboards to provide insights and key performance indexes to the leadership team

• Curated visualizations for a Luna Outcomes white paper project that focus on impact of Luna’s service on Pain Reduction

• Worked with the clinical leader and product owner to develop ongoing/continuous visualizations to track trends, identify gaps and drive new initiatives

Accenture, Mumbai, India Nov 2016 - Aug 2018

Software Developer

• Leveraged and queried Oracle DB to extend back-end application, build business reports and visualization modules using Tableau

• Developed front end of multiple components using JavaScript, CSS and Thymeleaf

• Worked extensively to develop services and views as a part of the development team using Java Spring MVC

• Reviewed audit module for bugs, applied remediation procedures to effectively alleviate issues and responsible for its delivery

Education

Northeastern University Sep 2018 – May 2020

Master of Science in Information Systems

Relevant courses: Data Science, Web Design, Machine Learning in Finance, Data warehouse and Business intelligence, Big Data and Governance, UI/UX

University of Mumbai, India May 2012-May 2016

Bachelor of Engineering in Computer Science

Projects

Retail Store Analytics (Talend, Tableau, PowerBI, Postgres)

• Designed an ETL pipeline to integrate the retail store data from diverse sources such as MSSQL, Postgres SQL, Oracle, MySQL

• Created source to target mappings to extract, load facts and dimensions into warehouse with transforms such as filter, joins

• Performed Data Integration with 4M+ rows of data involving data-conversion, error handling, loading erroneous records in rejects table, source to target mapping also created dashboards to demonstrating inventory, overall sales and rejects Analyzing Fintech Hiring Trends (Python, Docker, NLP)

• Scrapped Bank’s career portals and found the trends in fintech hiring industry for different job categories

• Extracted the top fintech related buzz words using various text extraction algorithm like text rank, TF/IDF and word count

• Visualized trends of popular job postings on the web in form of word clouds and other matplotlib graphs and used Natural Language Processing to determine top key words in trending posting, Dockerized image and deployed iT Finding Text Toxicity and Toxic twitter accounts (Python, EC2, Flask, Tweepy)

• Utilized AWS EC2 to fetch and deploy flask application with a large data of text and then cleansed it to remove any anomalies

• Filtered toxic text using prediction models using k-means, naïve bayes, linear regression algorithms and displayed Visualization

• Predicted toxicity of a twitter account by fetching tweets using an API and leveraging Models created Law firm client Filter (MSSQL, Toad)

• Designed a data model for a law firm client filter using Toad Data Modeler and formulated 32 business rules

• Created database MSSQL using complex SQL queries, trigger, stored procedure, views to check the ACID property

• Created and maintained different users and access rules based on who the end user is

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