https://www.linkedin.com/in/saurabh-pathare-057422117/ email@example.com EDUCATION
Carnegie Mellon University (CMU), Pittsburgh, PA May 2019 Master of Information Systems Management (MISM – Global Track) Relevant Coursework: Distributed Systems, Applied Data Science, Data Mining, Data Focused Python, Data Warehousing, Statistics for IT Managers, R for Data Science, Big Data and Large-Scale Computing, Data Science for Product Managers Dwarkadas J. Sanghvi College of Engineering (DJSCE), University of Mumbai, India May 2017 Bachelor of Engineering in Electronics and Telecommunications SKILLS
Programming: SQL, Python, R, Java, MATLAB
Data Analytics: Tableau, Weka, SAS, ETL, Microsoft SQL SSIS and SSAS, OLAP and ad-hoc query tools, IBM Watson Machine Learning: Decision Tree, Logistic Regression, Classification, Bayesians Algorithm, Neural Networks, Random Forest Libraries: Pandas, NumPy, MatplotLib, scipy, scikit-learn (Python), ggplot2, dplyr (R) Tools: Netbeans 8.2, Anaconda, Spyder, Jupyter Notebook, Oracle 11g, Android Studio, Minitab ACADEMIC PROJECTS
Cost of Curb (Assessing Price Analysis) – Capstone Project, Govt. of Pittsburgh January 2019 – May 2019
• Evaluating congestion patterns by using SQL and analyzing historic permit, parking revenue and occupancy data while deciding top predictors for congestion using regression models run in Python scripts.
• Developing a dynamic “pricing congestion” for parking, curbside loading access and traffic obstruction penalty based on inputs and weights of various predictors.
• Recommending strategic decision-making framework for providing solutions which tackles problem of allocation of curb to dedicated transit or bike infrastructure.
Pittsburgh Healthy Ride - Data Warehouse solution, CMU November 2018
• Served full cycle BI system and reported peak bike usage hours, frequently used bike routes and proposed strategies for monetizing customers for healthy bike ride.
• Designed warehouse solution using definitions, ETL logic and created business reports using SSIS, SSAS and OLAP cube.
• Scaled the data warehouse from 200,000 records to 20 million with an accuracy of 86% for extrapolation of big data. Customer Retention and Monetization Analysis – Data Mining Approach, CMU October 2018
• Retrieved real-world data from GradeSlam Inc. and analysed using Tableau, Python and Predictive Modelling for establishing the key factors leading to decrease in customer retention of Education website.
• Proposed strategies for solving the problem of customer retention and eliminated drawbacks in user interface which resulted in attracting more customers and increasing overall customer monetization by 31% Donor Segmentation and Strategy – Data Mining Project, CMU May 2018
• Analysed a dataset with 10M+ records using MySQL, Python and Weka and determined donor segmentation using k- means clustering various fundraising marathon events in the United States.
• Recommended pricing and publicizing strategies for tackling the problem of declined donations by performing data visualization in Tableau and IBM Watson.
Database structure design and Data Manipulation, CMU April 2018
• Designed the complete database schema, used normalization techniques and enforced data integrity constraints.
• Developed SQL script and executed analytic queries for building managerial reports on H.R. spending using Oracle 11g. WORK EXPERIENCE
Worksorted Pty Ltd, Adelaide, Australia May 2018 July 2018 Data Science Intern
• Utilized multivariate Monte Carlo Analysis for performing risk and uncertainty analysis of financial dataset and improved the accuracy of forecasting customer's monthly revenue by 43%.
• Identified customer groups with similar tastes and preferences by using Naïve Bayes classification.
• Applied Association Rule algorithm which recommended different products to customers by altering the business strategy and re-structured the revenue model.
• Spearheaded the deployment of new updates to all employees using SLACK and diminished existing inefficiencies. P.T. Instruments, Mumbai, India December 2015 January 2016 Data Analyst Intern
• Imported, manipulated and exported large data sets in under tight deadlines using SQL, MS Access and Excel (Pivot tables)
• Manipulated files and their associated data for rapid delivery to clients and automated repeatable tasks thereby enhancing the speed up to 63%
• Derived causal relationships between ordered and faulty connectors to predict future demands by using regression models. LEADERSHIP & CERTIFICATION
• Completed Scrum Master – PSM I online certification from Scrum.org 2018
• Spearheaded technical presentation on brand awareness of Credit Suisse in financial articles, New York. 2018
• Led a team of 8 and won the International cultural dance competition held in CMU, Adelaide, Australia. 2018