847-834-5564
Abhishek Mote
About
Hello, connections! I am an experienced Business Analyst, who loves playing around with the data to find every possible solution for the problem.
I have 3 years of experience working as an analyst in the customer service domain, from being a great team player to a good team leader, from solving customer queries to writing SQL queries.
Key Skills: SQL, PowerBI, Python for Data Analysis, AWS, and Machine Learning.
I am a Northwestern University grad student seeking full-time opportunities as Project Manager, Product Manager, Technical Program Manager, and Business Analyst.
During my curriculum, I have taken relevant courses: Project Management, Agile, Managerial Analytics, Statistics, and Data Analytics using R, Python for Data Science, Applied Data Science, Computer Systems, Data Science for Business Intelligence, Enterprise Data Science, and Data Warehousing.
My Experience
Roles & Responsibilities
January 2023 - Present
Global Mobility Services
● Developed and maintained Cloud Radio Access Network (CRAN) planning web application.
● Saved 15 hours weekly by implementing agile methodologies with JIRA for CRAN project management.
● Performed QC for the newly developed CRAN portal for ILWI and Ohio region.
● Developed python scripts utilizing the Pandas library to efficiently manipulate and transform data.
● Created automated data processing pipelines that involved extracting, cleaning, and transforming large datasets.
● Analyzed and tuned complex SQL queries to improve efficiency and enhance database performance.
● Created documentation for the CRAN web application to facilitate smooth onboarding and usage by a team of 10+ individuals.
August 2022 - October 2022
Data Analyst Intern, Berkshire and Spencer Consulting, NYC
● Collaborated with the R&D team for the development of ‘Love-Together’ iOS & Android application
● Attended scrum meetings for daily and weekly tasks and used Jira for task allocation, completion maintaining 100% transparency
● Wrote readable and understand python codes in Jupyter notebook for text mining, further used by a team of 10+ members
● Applied TF-IDF to find the frequency of the words for further analysis
● Applied Chi-Square analysis, finding correlation among 50+ words
April 2022
Extern, Invenergy LLC, Chicago
● As an extern at Invenergy, I got to be a part of the performance analytics team, to understand the working of power generation through renewable energy resources.
● Developed learning on MLOps and transfer learning for deep learning CNN model
● Applied transfer learning on the CNN model for crack detection in turbines to reduce the maintenance cost by 15%
● I got to understand how the company leverages the power of Data Science and Machine Learning to solve the real-time issues in wind farms.
● I got to learn about multiple ML projects being developed, and the kind of problems ML is capable of solving
January 2021 - July 2021
Business Analyst, TaskUs
● Built BI, reports, dashboards, analyzed for data driven business solutions saving resource utilization by
up to 2.5x
● Designed dashboards for monthly reports as a business strategy, leveraged visualization to increase
customer satisfaction by 50%
● Reviewed impact of features by analyzing wide range of data for client and increased productivity by
15%
● Interpreted data and revamped results using statistical data techniques cutting down data cleaning by
50%
● Gathered data to help and compose monthly reports of operations and monitored performance of 5+
people
● Designed SQL queries using stored procedures leading to 10x increased query performance
August 2018 - January 2021
L2 Associate(Analyst), Amazon
● Uncovered and solved challenges thereby promoting leadership principles by 100%
● Improved operational efficiencies while managing customer requests reducing the wait time by 15%
● Cultivated customer loyalty, reduced repeat customers and returns rate by up to 60%
● Analyzed customers data to identify problems, develop a potential solution and ensured high-quality service
● Managed a team of 10+ associates as an SME and maintained the production metrics to 90%
Education
My Studies
September 2021 - December 2022
MSIT, Northwestern University
-
Grade: 3.75/4.0
-
Activities and societies: Henry Crown Sports - Operations Team
-
MEM 410 - Managerial Analytics
- MSIT 421 - Computer Systems: Architecture, Organization, and Software
-
MSIT423 - Data Science for Business Intelligence
-
MSIT 431- Introduction to Statistics and Data Analysis
-
MSIT 443 - Technology Strategy & Enterprise Architecture
-
MSIT458 - Information Security and Assurance
-
CIS_323-DL - Python for Data Science
-
CIS_324-DL - Applied Data Science
-
CIS_325-DL - Enterprise Data Science
August 2012 - June 2016
B.E. RGTU
Studied Mechanical engineering, majoring in Design and drawing of machine parts and elements critical to manufacturing
Participated in National Go-kart Championship
Published a research paper in IRJET on Heat dissipation through the fins of an air cooled IC Engine
Skills
Professional Competencies
MySQL
MS SQL/ SSMS
Python for Data Analysis
Tableau
R for Data Analysis
Azure VM for Machine Learning
MS Excel
ML Flow
My Projects
Gender Detection API
Developed CNN model for facial detection in TensorFlow serving and keras and containerized using Docker.
Created REST API and flask in Visual Studio, using HTML for front end API, resulting in 98% accuracy in prediction
Traffic Sign detection for Self-Driving Vehicle application
Conducted EDA and applied CNN model on German Traffic data set on Azure Virtual Machine
Tested model on 10,000 test images and tracked model performance on ML Flow
Cereal Segmentation Analysis
Applied PCA on the dataset and used cluster analysis to segment the cereals into identifiable clusters
Used f_viz and ggplot2 to visualize the clusters based on PC1 and PC2
Charity Organization Prediction
Conducted multivariate analysis on explanatory variables for donor and surmised likelihood of each donor
Proposed exploratory data analysis on 50+ data point, used hyper parameter tuning to pick the best predictors using Select K best, applied ML Flow to track the model for regeneration
