Shyam Krishnan

Shyam Krishnan Shyam Krishnan - | Chennai, India |-| LinkedIn: shyam-krishnan | Github | Tableau EDUCATION MS, Information Systems University of Maryland, Robert H. Smith School of Business B. Tech (Distinction), Electrical and Electronics Engineering Amrita University, Coimbatore Graduated: December 2019 Maryland, USA Graduated: August 2016 Tamil Nadu, India PROFESSIONAL EXPERIENCE ❖ Amtrak, National Railroad Passenger Corporation – Washington, DC, USA May 2019 – December 2019 • IT Reporting & Financial Analyst Intern, Passenger Information Display Systems ▪ Developed budgets, reconciliations and actuals reports using SAP Concur showing the incurred charges against all ongoing projects funded by Federal Railroad Administration typically ranging from $250K to $25M annually ▪ Created an Invoice Management dashboard in Tableau that helps six project managers efficiently approve invoices received from third party vendors assisting streamlined payment process for Amtrak Finance reducing the unpaid invoice backup 20% month on month ❖ ZoomRx Healthcare Solutions, Chennai, Tamilnadu June 2017 – March 2018 • Associate, Pharmaceutical Market Research ▪ Enabled a fortune-500 pharmaceutical client to make better decisions on their drug value creation and their brand perceptions through an in-house survey based analytical techniques with the help of SQL, advanced Excel functions and visualized the insights on a Tableau Dashboards to drive business insights ▪ Initiated recommendations from responses obtained from surveys; improved client’s physician reach by 25% ▪ Automated physician responses status of surveys using Google Scripts and SQL ❖ Mu Sigma Inc., Bangalore, Karnataka • Trainee Decision Scientist – Marketing Solutions October 2016 – April 2017 ▪ Led a team of five people and coordinated with a $50B pharmaceutical client by helping revamp marketing campaign strategies to increase older drug sales facing a dip in revenue due to market cannibalization ▪ Developed statistical models using predictive and prescriptive analytics; Utilized exponential smoothing time series models to visualize sales forecasts which resulted in revenue growth by 25% ▪ Built a Microsoft Excel dashboard to solve a route optimization problem for a major courier services company • Decision Scientist Intern - Center of Excellence & Innovation January 2016 – May 2016 ▪ Developed a Python script for streamlining an end-to-end business analytical process and automating report generation and updating data quality issues for the world’s largest apparel manufacturer using Python and Tableau ▪ Improved quality of decision making; decreased delays in report generation by 80% ▪ Appreciated by client, team lead and manager for driving this project towards completion and diligence shown towards tasks assigned VOLUNTEER EXPERIENCE ❖ ChangingThePresent.org, New York City, NY, USA April 2020 – February 2021 • Volunteer, Analytics Lead ▪ Responsible for hiring and training 15+ analysts on Google Workspace ▪ Executed data-driven strategies for non-profit organizations signed up on the platform ▪ Built automation tools using Jotforms, Python and GCP for creating influencer pages on our websites BUSINESS & TECHNICAL SKILLS Programming Skills: Databases / Big Data: Tools / Frameworks: Cloud Computing: Data Visualization, Reporting: Team Collaborative Tools: Business Management Skills: Python, R, Web Design & Development (HTML, CSS, JavaScript, BootStrap) MS SQL Server, Hadoop File Systems, MongoDB, SAP, StatTools Git, Pandas, NumPy, Matplotlib, Seaborn, NLtk, Scikit-Learn Amazon Web Services, Google Cloud Platform Microsoft Excel, PowerPoint, Tableau Desktop, RShiny App Microsoft Project & SharePoint, Asana, Google Workspace Client Relations, Strategic Decision Making, Critical thinking, Problem Solving Page 1 Shyam Krishnan ACADEMIC DATA SCIENCE PROJECTS ❖ Yelp Data Challenge: Predicting Star Ratings (Big Data Systems) March 2021 –April 2021 ▪ Leveraged big data technologies such as AWS Sagemaker by implementing Machine Learning models on the Yelp Dataset which comprised of 6.6M reviews across 200K businesses by setting up a Zeppelin instance for analysis ▪ Built functions using Apache Spark for data cleaning with an increased execution speed by 30% ▪ Support Vector Machine Regression was the best model for our analysis which could predict the star-rating with an 85% accuracy ❖ Hiretual Data Challenge: Corporate Attrition Predictor (Data Mining) March 2021 –April 2021 ▪ Spearheaded a team of 4 for analysis and modelling of Hiretual’s recruitment data to predict the attrition rate of employees in various businesses and non-profit organizations based on available and extrapolated features ▪ Developed data processing/ cleaning pipeline in python to efficiently handle ~10GB of data in Jupyter Notebook ▪ Used tests of significance and multicollinearity to streamline feature selection. Developed logistic regression, SVM and Random-Forest classifier, achieved 80% accuracy with Random Forest model ❖ Traffic Violations Predictor: Montgomery County, Maryland (Accessing web-data) March 2021 –April 2021 ▪ Implemented the Data Analysis workflow in RShiny from Descriptive to Prescriptive analytics using the open-source data on traffic violation cases in Montgomery County in the State of Maryland ▪ Built a prediction workflow of traffic violation cases across months in 2019 using ARIMA Time Series technique ❖ Efficiency Analysis of Public Utility Vehicles, Maryland (Decision Analytics) April 2021 –May 2021 ▪ Led a team of 3 for analysis of the fuel efficiency of public utility assets for the city council of College Park, Maryland ▪ Presented our analysis on low, medium, and high duty vehicles across different seasons to the College Park Mayor ▪ Conducted awareness campaigns to essential and emergency services teams on the importance of ‘code-orange’ days to save the environment from pollution by low fuel-efficiency vehicles ❖ Customer Segmentation Analysis: Product Marketing (Decision Analytics) April 2021 –May 2021 ▪ Customers who have made recent purchases from an online retail store were analyzed and segmented into various categories based on their profiling details to enable the online retailer to improve their shopping experience on all customer touch points ▪ The insights generated from the customer segmentation analysis were put up in an interactive storyboard in Tableau Public ❖ Page Rank Analysis: Python Data Visualization (Data Mining) April 2021 –May 2021 ▪ Built a simple web-page crawler in Python that accesses all the links in a webpage stored in an SQLite database for computation of Page-rank ▪ The resulting page-ranks of the links in the website are visualized using d3.js which is a JavaScript library for data visualization COURSES & CERTIFICATIONS ❖ Academic Courses ▪ Data Science ▪ Data Analytics ▪ Accessing Web-Data ▪ Financial Management ▪ Project Management ▪ Big Data Systems ❖ Other Courses & Certifications ▪ Python Specialization (University of Michigan) ▪ Tableau Desktop Specialization (UC – Davis) ▪ Business Foundations (Wharton – UPenn) Page 1