Aishwarya Gunde
Data Analyst, Commercial Data Science at Abbott
Data Scientist at Zoetis Inc.
Abbott
https://www.linkedin.com/company/abbott-
Data Analyst, Commercial Data Science
• Pioneered advanced analytics techniques at APOC in understanding customer base, ordering patterns, measuring loss and declining, leveraging external market data integrated with internal data to gain insights on customer behavior, building risk models, and as a result, recommending strategies to retain at-risk and lost customers.
• Received DVP Platinum award for pioneering contribution in analytics and commercial decision making.
New York City Metropolitan Area
https://media-exp1.licdn.com/dms/image/C560BAQHOkTAbXwQjcg/company-logo_100_100/0/1625141088050?e=1655942400&v=beta&t=fX-zEvgPzNx_3rmevXlqj4IVeG7-p-Lab319z4luvJQ
Abbott
https://www.linkedin.com/company/abbott-
Data Analyst Intern
Performed Clinical Research analysis involving data cleaning, transformation, integration, statistical and exploratory analysis in R(Markdown, Knit for automated study reports) for assay testings.
New York City Metropolitan Area
https://media-exp1.licdn.com/dms/image/C560BAQHOkTAbXwQjcg/company-logo_100_100/0/1625141088050?e=1655942400&v=beta&t=fX-zEvgPzNx_3rmevXlqj4IVeG7-p-Lab319z4luvJQ
New Jersey State Police
https://www.linkedin.com/company/new-jersey-state-police
Data Science Externship (Rutgers PSM)
Analyzed the ballistics intelligence data of the National Integrated Ballistics Information Network (NIBIN) database established by the Bureau of Alcohol, Tobacco and Firearms and Explosives (ATF), and GunOps. Built predictive models for the range of next crime duration and location related to the same ballistics. Received fellowship award from the Rutgers Professional Science Master’s program for contributing to this project.
Hamilton, New Jersey
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Ortho Clinical Diagnostics
https://www.linkedin.com/company/ortho-clinical-diagnostics
Data Science Externship (Rutgers Advanced Analytics Practicum)
Using text mining methods, analyzed the customers' unstructured complaint data to identify and cluster the problems and root causes, followed by predicting the required time period to resolve a specific subject-related complaint, to drive product insights and improve solutions.
New Brunswick, New Jersey
https://media-exp1.licdn.com/dms/image/C4E0BAQFWjUgzgdzZsA/company-logo_100_100/0/1619032549827?e=1655942400&v=beta&t=KPKf6nXkhWry1zv3iT77clhsDPsuHdkeJR2BXJdppa4
Data Science and Analytics
Master of Business and Science
Rutgers University
https://www.linkedin.com/school/rutgersu/
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Digital Marketing
Executive Education: Mini MBA
Rutgers Business School
https://www.linkedin.com/school/rutgers-business-school/
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Information Technology
Bachelor’s Degree
Walchand College of Engineering, Sangli
Fellowship Award - New Jersey State Police Ballistics Forensic Project
Rutgers University Professional Science Master's Program
Advance Database Engineering
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Data Mining
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Data Structures and Algorithms
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Information Storage Management
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Linear Algebra
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Statistics and Fuzzy System
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Unix Operating System
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Advanced Analytics Practicum
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Analytics for Business Intelligence
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Big Data and Cloud Computing
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Digital Marketing
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Fundamentals of Analytics
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Massive Data Mining
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Mobile App Development
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Natural Language Processing
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Principles of Finance and Accounting
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Python for Data Science
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Regression Analysis
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Science and Technology Management Capstone
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Special Problems in Business and Science
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Multivariate Time Series Forecasting for Ambient Intelligence Research
▪Built Recurrent Neural Network (RNN) on the multivariate time series data sensors retrieved by the smartwatch.
▪Predicted indoor localization using the LSTM model by converting the time series data to supervised learning, evaluated the
model using RMSE, and rescaled the result back into original units using keras and sklearn libraries in Python.
Product Recommendation in E-Commerce
▪Predicted ratings using matrix factorization (SVD), kNN, ALS, and SlopeOne algorithms and evaluated based on RMSE, MAE, Precision, Recall and F-measure while also implementing implicit feedback learning approach using SVM in Python.
▪Implemented Hadoop MapReduce for ranking similar items and users using cosine, jaccard and pearson similarities.
▪Addressed cold start problem using co-clustering and simultaneously learning algorithms in Python.
▪Conducted text-based approach using vectorization and feature extraction on text review by Gensim, NLTK in Python.
▪Conducted image-based approach by implementing representation learning on image feature vectors using MLP in PySpark.
Big Data and Cloud Computing
Predicting Success of Bank Direct Marketing Campaign
Digital Marketing
Mobile App Development: Happy Abode
Built an Android application for maintenance request management for property managers and residents;                                  inclusive of smart and quick features, such as image capture, to file the requests and curb paper work.
Python for Data Science: Global Economy Network and Cross Country Analysis
Analyzed economic growth of large data sets of countries based on Gross Domestic Product by implementing Regression Analysis concept using science and stats libraries in Python.
Big Data Analysis: Detection of Suspicious Activities through Video Surveillance
Managed and analyzed huge amount of video data in order to detect and alert about suspicious activities in an area through video surveillance using MATLAB.
https://github.com/aagunde/Big-Data-Analysis-Video-Surveillance
Data Visualization with Tableau
Udacity
https://www.coursera.org/account/accomplishments/verify/M9DNQ3HQJ2YZ
Big Data Analysis with Scala and Spark
M9DNQ3HQJ2YZ
www.coursera.org
Coursera
Mini-MBA in Digital Marketing
Rutgers Business School Executive Education
Data Mining with Weka
The University of Waikato
Data Scientist’s Toolbox
Johns Hopkins University School of Education
https://www.linkedin.com/in/harsha-polisetty
Harsha Polisetty
Data Scientist at Zoetis | Problem Solver | Strategist
New York City Metropolitan Area
https://www.linkedin.com/in/walt-mancini-2762106
Walt Mancini
General Manager US Outpatient at Abbott
Ridgewood, NJ
https://www.linkedin.com/in/sherrypudloski
Sherry Pudloski
Senior Consultant, Former EVP, Head of Corporate Affairs and Communications at Zoetis Inc. & Chief Communications Officer at Guardian Life
Chatham, NJ
https://www.linkedin.com/in/aparna-mohan-856aab103
Aparna Mohan
Business Intelligence Engineer @Amazon
New York City Metropolitan Area
https://in.linkedin.com/in/saurabh-melge-911b40168
Saurabh Melge
Software Engineer at Veritas Technologies LLC
Pune
https://www.linkedin.com/in/vrishalikulkarni
Vrishali Kulkarni
Actively seeking job as a Data Scientist
Buffalo, NY
https://www.linkedin.com/in/dasvenkatesan
Das Venkatesan
Senior Data Scientist at Zoetis Inc.
Hackettstown, NJ
https://www.linkedin.com/in/srisakthi-r-627406a3
Srisakthi R.
Data Engineer
San Francisco Bay Area
https://in.linkedin.com/in/sheetal-powar-97b015229
Sheetal Powar
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Kolhapur
https://in.linkedin.com/in/rohan-jadhav-145b6944
Rohan Jadhav
React Native Developer
Sangli
https://in.linkedin.com/in/priyanka-tukan-0ba5b2154
Priyanka Tukan
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Kolhapur
https://www.linkedin.com/in/vickie-king-97105424
Vickie King
Associate Director at Zoetis
Kalamazoo, MI
https://www.linkedin.com/in/krystinatansey
Krystina Anderson
Veterinary Clinical Research Associate at Zoetis Inc.
Richland, MI
https://www.linkedin.com/in/siddhi-doshi-442b77a2
Siddhi Doshi
Student at Northeastern University
Boston, MA
https://www.linkedin.com/in/purishubham
Shubham Puri
Social Insights Analyst at Vaynermedia | Data Scientist | Business Intelligence | Data Engineer | Machine Learning Practitioner | UIC | MSBA Graduate
Greater Chicago Area
https://www.linkedin.com/in/lianghui-li
Lianghui Li
Data @ Robinhood
San Francisco Bay Area
https://www.linkedin.com/in/shriya-rao-msba
Shriya Rao
Business Insights & Data Analyst at Amazon Web Services (AWS)
Santa Clara, CA
https://www.linkedin.com/in/namitsingh12
Namit Singh
Data Nerd | Business Analyst | Data Science enthusiast
Plano, TX
https://www.linkedin.com/in/sagarvasaikar798
Sagar Vasaikar
Actively looking for Full-Time Job opportunities Data/Business Analyst | Data Scientist | BI Analyst | Product Analyst
New York City Metropolitan Area
https://nl.linkedin.com/in/anjanagopan
Anjana Gopan
Data Analyst at Material in Motion | Data Analysis | Business Intelligence
Amsterdam
LinkedIn User
      
          



            
              
        
              
  

    
        Aishwarya is a skilled Data Scientist working in R, Python and SQL, while effectively collaborating with Sales, Marketing, Salesforce Operations, Finance and IT. She has leveraged her skills across projects of varying complexities, e.g., identifying untapped opportunities, predicting customers at risk of churning, and building algorithms to inform the development of the Customer Master.  Additionally, Aishwarya has built performance reports and dashboards in Excel and Power BI that integrated Sales and CRM (Salesforce.com) datasets.  In addition to her technical and collaborative skills, Aishwarya is proactive and innovative, often bringing forward new ideas and approaches that could lead to deeper insights for her business partners.  Christie Nelson, Ph.D.
      
          



            
              
        
              
  

    
        I have taught Aishwarya in several graduate courses, and she has worked on several research projects for me through the Rutgers MBS Externship Exchange (mbs.rutgers.edu/externships) and the MBS analytics practicum. She is very conscientious, and always produces very high quality work. 

The project that stands out is one that she and two other MBS students worked on for me in partnership with the NJ State Police Forensics Lab. This was a ballistics data analysis project, utilizing machine learning (predictive and unsupervised models), data visualization, descriptive data analysis, and data cleaning techniques. The work was so successful, that Aishwarya and her 2 teammates first presented directly to the NJ State Police, then later to a group of ~50 practitioners including the ATF, state and local law enforcement, a county prosecutor's office, the Police Foundation, the Center on Policing, CCICADA.org, and more (https://mbs.rutgers.edu/articles/ballistics-analysis-project-externship). It was then presented to NJ Ballistics Community of Interest working group meeting (May 2018). This work was most recently cited in an Aug 2018 report done by the National Crime Gun Intelligence Governing Board (https://crimegunintelcenters.org/wp-content/uploads/2018/09/CGI-Manual-Best-Practices-ATF-27-AUG-18.pdf). The long reach of her work really speaks to the quality and dedication that she put into this project, and all others that she works on. I highly recommend her!