About me

Akshay is presently employed as a Software Engineer, for a multi national corporation in Maryland, United States. He works on all aspects of software engineering, data engineering, ETL pipeline development, and SQL development, with expertise in SQL query tuning and optimization techniques. Akshay has a MS degree in engineering management, with a focus on database administration and data science, a graduate of the University of New Haven

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Software Engineer - CareFirst

April 2022 - Present

Currently Akshay works for BlueCross BlueShield of CareFirst in the Facets System Integration team, where he assists in development of data interfaces, system integration, reporting, and development for Facets extensions, batch processing engines. Akshay is proficient in technologies such as C# .NET, Python, Apache Spark, PySpark, Spark SQL, MS SQL Server, SSIS, Tableau

Manager - Healthcare Analytics - EXL Service

Oct 2021 - April 2022

Akshay worked for EXL service in the Healthcare Analytics team, where he assists in data modeling, integration, reporting, and analytics for Medicare Risk Adjustment products and solutions. His objective is to enhance performance, make logical data-driven decisions, and save costs. Akshay is proficient in technologies such as MS SQL Server, SSIS, SSRS, Tableau, R, and Python.

Associate Data Analyst - Blue Cross Blue Shield Association

June 2020 - Oct 2021

Akshay worked in the data warehousing team, helping in creating ETL data pipelines for HEDIS data integration, by extracting from multiple sources, transforming and loading billions of volumes of data to data warehouse. Akshay is also expert in data analysis, identifying discrepancies in HEDIS data, transforming the data to chunks of information and transforming the information to valuable insights. Akshay worked as a functional overlap between Data Analytics, Data Engineering and Product management. Akshay is skilled in technologies like MS SQL Server, SSIS, SSRS, Tableau, R and Python.

Projects

Take a look at my recent work!

Data Cleaning & Pre-processing - Medicare Claims

The datasets is provided by the National Cardiovascular Disease Surveillance System. Its integrated from multiple indicators from many data sources to provide a comprehensive picture of the public health burden of CVDs and associated risk factors in the United States. Explored the data for anomalies in order to prepare it for analysis. Using the seaborn library, I visualized the data to find the missing value. Identified and de-duplicated the data to improve accuracy and efficiency. Analyzed the data to identify numerator drop, explored the states and the claim associated with it. Identified and handled missing values successfully using pandas and the numpy package. The data was also grouped to split, apply, and combine based on category buckets for analysis and exported to an excel file. (Python libraries used: Pandas, NumPy, Seaborn)





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Web Scraping Crypto Prices using BeautifulSoup Python

Retrieved the HTTP get requests and saved the response. Fetched crypto prices by web scraping through BeautifulSoup library in Python. Created loops to automatically trigger every few minutes, scrapes the price and loads it to CSV file. Utilized smtlib library, to automatically notify the user through an email if price falls between certain price range














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