Mayank Sundriyal adql1z@r.postjobfree.com LinkedIn

Hartford, CT, 06105 860-***-****

Experienced Data Analyst /PM skilled in storytelling, automating, developing, and compiling reports and dashboards using BI Tools. Adept knowledge in PM, data analysis/ science, and data visualization. Proficient in Tableau, Python/R, SQL, and Machine Learning. Education:

University of Connecticut -School of Business Sep 2021-Present Master of Science in Business Analytics & Project Management Major: Data Science Environments:

Languages: R, SQL, Python (Pandas, Matplotlib, Seaborn, PyTorch, Scikit-Learn, and Numpy). Databases: Oracle 11g, Microsoft SQL Server, Teradata. Tools: Tableau, Visio, SAS JMP, R Studio, Jupyter Notebook, MS Project and Excel, Google Analytics, Workbench, Apache Spark. Statistical and Predictive Modeling: Statistics in Business Analytics, Data modeling, Linear/Logistic Regression, Ensemble (Bagging, Boosting), Naïve-Bayes, KNN, Neural Networks, Clustering, Correlation, Principal Component Analysis, Machine learning algorithm. Analytical Skills/Management: Data Cleansing, Data Mining, Data Warehousing, Business Intelligence, Data Visualization, Segmentation, Hypothesis Testing (t-test, Chi-Square), Sampling, Probability Distribution, Project Management, Project Risk and Cost Management, Advanced Excel (Pivot Tables, VLOOKUP), CRM, Salesforce Lightning, A/B Testing, Market research. Experience:

Infosys (Pfizer & Bank of America) – System Engineer April 2020 – Aug 2021

● Automated Python-based ETL pipeline to extract data on regular basis utilizing Pandas, Scikit-Learn, and Numpy libraries.

● Collaborated with the Cross-sell strategy team for system testing and supervised hyper care support for the users, by giving optimal solutions which increased the efficiency by 30%.

● Analyzed client’s business requirements and processes through data analysis, user feedback, and workflow analysis.

● Created Tableau scorecards, dashboards using stack bars, scatter plots, geographical maps using show me functionality.

● Used SQL, SOQL, and SOSL query to generate reports on E-permission, Sales Area to Customer, and Salesforce to Sales Area.

● Increased accessibility & usability of customer data by redesigning data visualization techniques to include statistical graphs and information graphics which decreased the manual intervention by 15%.

● Developed the Gantt chart in Microsoft Project illustrating event schedule, assigning resources to tasks, tracking progress, and managing the budget. Also assisted in the portfolio management of existing client portfolios. System Engineer Trainee Nov 2019-March 2020

● Created SQL queries with optimized joins and window functions, which quickly increased reports retrieval by 45%.

● Extracted data from ArcGIS & GTFS, performed segmentation, and clustering to make real-time dashboards on Tableau & Excel.

● Lead a team of 5 people to build a python Django web app with Angular which can be used by teams of developers.

● Integrated the code & designed the overall flow of the application using JAVA EE and Frameworks like AngularJS, Bootstrap, MongoDB. Developed a plan using marketing analytics to increase viewership on the website and help them gain viewers and new members, in conjunction with other social media outlets. The improved website traffic of the client through data analysis using Google Analytics, A/B testing by 60%.

Projects:

Insurance Customer Data

• Developed a machine learning model using multiple linear regression to predict the probability of the insurance price in a sample of 5000 records with an accuracy of 87% and determine the magnitude with which attributes like the year of experience, past accident history, education level, vehicle model year and gender affect the price of insurance. Budget approval process

• Created the database and budget request of the budget process for multinational enterprise with a portfolio of more than 10 beverage brands using the Swim Lane, ERD diagram, and performed complex SQL queries to get the reports like the total budget request and total approved budget by brand wise, the total value of purchase requests per marketing activities and the total time (in days) required for a request to be finally approved. Machine Learning with Python

• Employed spot-checking of machine learning algorithms to get a quick assessment of the performance of algorithms like Logistic Regression, Random Forest, Decision Trees, KNN, and Naïve Bayes in predicting whether it will rain in Australian cities and identified the best algorithm to work with (Random Forest Classifier) based on its sensitivity and specificity.

• Performed hyperparameter tuning of random forest classifier model to increase its accuracy by 0.18% to 76.85%. Supra Sae India

• Lead a team of 25 highly technical members to compete in the student vehicle formula championship and won 3rd prize for the innovation in the air intake. Facilitated and trained the 200 engineering students on sensor technology.