www.linkedin.com/in/MM2020 https://github.com/mayurimagdum/MachineLearning email@example.com TECHNICAL SKILLS
Data Management : Data Analysis, Pattern & trend identification, Visualization of data insights. Analytics Tools: R, Python, Tableau, Power BI, SAS Visual Analytics, Advanced Microsoft excel,SPSS,MATLAB Database Management Tools: MySQL, QlikView
Software Development methods: Waterfall, Agile-scrum, RUP EDUCATION
Master of Science in Business Analytics University of North Texas, Denton, TX GPA: 4.0 May 2020 Bachelor of Engineering in Electronics & Telecommunication University of Pune, Pune, India GPA:3.8 May 2014 CERTIFICATIONS
1. AWS Certified Cloud Practitioner 2. Tableau Desktop Specialist 3. Python for Data Science 4.Text Analytics and Prediction with Python 5. Database and SQL for Data Science
Intern at Data Analytics and Research Institute, University of North Texas, Denton Texas Sept 2019 – Jan 2020
• Data preprocessing, exploration, visualization, and analysis of US federal occupational employment data to design business intelligence dashboards providing job market study to design coursework. Tools :SAS Visual Analytics,Python, Power BI
• Analyzed university student data to understand nontrivial reasons behind the attrition and identify students that are at risk of dropping out. The project resulted in 41% reduction in attrition rate. Methodologies: SVM, Logistic Regression,RandomForest Tool : Python(Sklearn,matplotlib,pandas,Numpy)
• Designed dashboard to explore academic profile, student enrollment, degrees awarded, graduation and retention rate, research expenditure, Alumni locations of the university. Methodologies: SAS Visual Analytics, Tableau Teaching Assistant University of North Texas, Denton Texas Aug 2019 – May 2020
• Assisting professor with designing the course (Python programming language & Data Visualization) syllabus
• Debugging and helping students understand the python program errors.
• Shadowing data science PhD students and professor in data preprocessing and data analysis on the ongoing projects in department
Network Data Analyst Ericsson Private Limited, Noida India Nov 2014 – Jun 2018
• Collaborated with the business analyst and developed Churn model using 1 million customer records and provided association rules to find specific conditions in which customers have left the company. This enabled the client to target current customers who satisfy those conditions and thus reduce churn significantly.
• Developed call drop prediction model using ANN algorithm with GSM QoS parameters data collected over 3 months to optimize the network and reduce call drop rate.
• Prepared infrastructure upgrade prioritization dashboard using call data, traffic utilization data and network parameters to find out the locations where infra condition is worst and based on number of technical support calls and find out underutilized sites.
• Worked closely with the data scientist to improve network performance using machine learning to predict the network failure using proactive approach. Resulting into 85% of reduction into the network outage incidents RESEARCH PROJECTS May 2019 – May 2020
• Collaborating on a research review paper on Knowledge Graph in the product recommendation and Voice Assistant applications, drug discovery and information extraction.
• Building an information retrieval system for legal firms using 40,000 commercial law cases collected from 50 states of USA. Methodologies: Bert Classification, Tools: Numpy, pandas, NLTK ACADEMIC PROJECTS Aug 2018 – May 2020
• Analyzed customer churn data from IBM repository and developed predictive model with 83% AUC to predict the customer churn and to find prominent groups of customers of the N/W. Methodologies: Logistic Regression Tools: Python(Sklearn, matplotlib, pandas, NumPy)
• Developed email text classification model to classify spam emails. Methodologies: Text Classification, NLP, Naïve Bayes model Tools: Python (Sklearn, NLTK, pandas, Numpy, matplotlib)
• Built customer segmentation model on the wholesale dataset with 10,000 customers and performed RFM analysis. Tools: Python (pandas, Numpy, matplotlib, Sklearn) Methodologies : K means clustering. Designed relational database for
‘Teachers pay teachers’ online portal where teachers can buy, share and sell their educational material. Methodologies: Relational database design, Data Visualization Tools: MySQL, QlikView, Power BI,