Aamir Goriawala
Senior Data Scientist at Progressive Insurance
Senior Data Scientist at Progressive | USC Viterbi 2016
Experienced Data Scientist with a track record of delivering business value through Data Science & Analytics. Awarded a Master's in Data Informatics from the University of Southern California, May 2016. 

- Proficient in preparing structured, unstructured and semi-structured data for Exploratory data analysis
- Experience in building Machine Learning & Deep Learning models to gain insights from large datasets
- Strong quantitative and analytical skills balanced with a business perspective
- Communicate results and educate through visualization dashboards & reports 
- Collaborate with a globally based team to efficiently drive product growth and satisfy customer engagement needs
- Excellent communication skills, written and verbal; ability to present results in a clear & concise manner to a  technical as well as non-technical audience
- Familiarity with Agile & Waterfall SDLCs, Scrum, Confluence & JIRA
- Self-motivated & thrive in a collaborative work environment


Technical Skills: Python, Matlab, R, SQL, NoSQL, Keras, Hive, Spark, ElasticSearch, Logstash, Kibana, Tableau, Splunk, AWS, Jupyter Notebook, Conda

Areas of Proficiency -  Classification, Regression, Clustering, Anomaly Detection, Dimensionality Reduction, Recommendation Engines, Data Mining, Data Visualization, Statistical Analysis, Text Mining, Natural Language Processing, Computer Vision, Time series analysis, Exploratory Data Analysis, ETL, Data Management, Information Retrieval, Web Scraping, Industrial IoT

Github - https://github.com/aamirg
Progressive Insurance
https://www.linkedin.com/company/progressive-insurance
Cleveland, Ohio, United States
https://media-exp1.licdn.com/dms/image/C4E0BAQH0HHOtey-eFQ/company-logo_100_100/0/1625147540375?e=1655942400&v=beta&t=Jk5M-EH8I5nmAR-OkoA75rgxVToIhaZskgh3mhytoaM
Senior Data Scientist
Garrett - Advancing Motion
https://www.linkedin.com/company/garrettmotion
• Garrett Motion was formerly known as Honeywell Transportation systems.
• Develop an Anomaly detection system to identify anomalies for Connected Vehicles and classify them as cyber-attacks or component faults
• Delivered on projects with four global automakers, securing future recurring business for the company in a new domain
• Analyze automotive network data to develop new algorithms and improve the detection capabilities of the system while reducing false positives
• Calibrate algorithm hyperparameters to build a representative model of vehicle behavior for different OEMs
• Automate hyperparameter tuning, effectively reducing the time & effort required to calibrate the system
• Prototype Security operations center for off-board analytics using Elasticsearch, Kibana & Logstash
• Partner with senior leadership to define product roadmap and perform feasibility analysis
• Present our technology in customer meetings attended by a technical and non-technical audience
• Seamlessly collaborate with global team members (US, Europe, China & Korea) to drive product growth and satisfy customer engagement needs 
• Actively involved in hiring and mentoring Data Scientists
Greater Atlanta Area
https://media-exp1.licdn.com/dms/image/C560BAQG0VpryvcIxIA/company-logo_100_100/0/1540554885457?e=1655942400&v=beta&t=NTyw2DpjJQnnDXaLmDjGScmnu1eixIfDTn_r0xd2pBs
Senior Data Scientist
Garrett - Advancing Motion
https://www.linkedin.com/company/garrettmotion
Garrett was formerly part of Honeywell, known as Honeywell Transportation systems. It was spun-off from Honeywell on 1st Oct 2018 to be an independent publicly-traded company ($GTX).
Greater Atlanta Area
https://media-exp1.licdn.com/dms/image/C560BAQG0VpryvcIxIA/company-logo_100_100/0/1540554885457?e=1655942400&v=beta&t=NTyw2DpjJQnnDXaLmDjGScmnu1eixIfDTn_r0xd2pBs
Data Scientist
Honeywell
https://www.linkedin.com/company/honeywell
• Develop an Intrusion detection system to identify anomalies for Connected Vehicles, in an agile environment
• Analyze automotive network data to develop new algorithms and improve detection capabilities of the system
• Implement automation scripts, effectively reducing the time & effort required to calibrate the system 
• Develop the parameter set for the algorithms, tailored to different configurations of vehicles from different OEMs
• Tune hyper-parameters for anomaly detection algorithms
Greater Atlanta Area
https://media-exp1.licdn.com/dms/image/C560BAQFvcIh3UnA5zw/company-logo_100_100/0/1535662846602?e=1655942400&v=beta&t=p_aUutEnO4h61Et9l7e80jBGTGQHV-jmJ6NO2jccCUY
Data Scientist
Yobs Technologies
https://www.linkedin.com/company/yobs
- Developed a SaaS solution that uses bias-free AI to help companies make smarter hiring decisions and coach teams more effectively.  Our system helps recruiters build accurate psychographic & emotional quotient profiles on candidates from their interview videos. We help companies discover high-fit candidates by looking beyond the resume & identifying their soft skills.
- Implemented a patented framework for Behavioral Signal Processing using supervised machine learning, which can predict the personality traits of a candidate from a short video interview.
- Built an end-to-end data science pipeline capable of performing:- data cleaning, feature extraction, model training, hyperparameter optimization, model deployment.
- Led the hiring process to grow our Data Science team.  
- Founded at Viterbi Startup Garage in 2016 
- Raised $1.3M from Flight Ventures, General Catalyst RDV along with other angel investors
- Grew to $500k ARR in 2018 with clients like Gucci & Hublot
Greater Los Angeles Area
https://media-exp1.licdn.com/dms/image/C560BAQHbdw1ZiHE39w/company-logo_100_100/0/1638394706856?e=1655942400&v=beta&t=ALIkxeE88lWi_34WBu8HerNNppAETMgw4u8vK_HfC5Y
Consultant Data Scientist
terra.ai Inc.
https://www.linkedin.com/company/terra.ai
Terra.ai is developing next-generation reservoir engineering solutions using machine learning
We have a full range of products that handle all dimensions of data from the oil field using both simulation and analytical models driven by our proprietary ensemble learning tech. 
Using entirely public data, we have built a system that forecasts the production of oil more accurately than a human at scale. When a geologic model is available, we have built processes around numerical simulation methods to calibrate property models and recommend optimal well placements. We are also building a line of data services to support these processes such as assisted data collection tools and visualization interfaces.
Greater Los Angeles Area
https://media-exp1.licdn.com/dms/image/C4D0BAQH0dgyIIhMC_w/company-logo_100_100/0/1519895190800?e=1655942400&v=beta&t=K8pGBLQ45gBjqep9Vfl90tUPZXu0oG0BrBETGE89mtk
Data Scientist
terra.ai Inc.
https://www.linkedin.com/company/terra.ai
Greater Los Angeles Area
https://media-exp1.licdn.com/dms/image/C4D0BAQH0dgyIIhMC_w/company-logo_100_100/0/1519895190800?e=1655942400&v=beta&t=K8pGBLQ45gBjqep9Vfl90tUPZXu0oG0BrBETGE89mtk
Data Science Intern
USC Marshall School of Business
https://www.linkedin.com/company/usc-marshall-school-of-business
• Responsible for implementing web scrapers in Python using Selenium & BeautifulSoup4 that scraped large volumes of data from multiple websites.
•  Retrieved all the listed information about companies from CrunchBase.com through their API. The data was parsed and stored in a MySQL database, for which I designed the ER model.
•  Scraped ~10GB of information about 1.2 million apps from Apptrace.com including their complete Sentiment and Ranking data which was stored in .json format. Retrieved app information about top ranking apps based on 36 categories, storing the information in CSV format. 
•  Retrieved app information from Distimo.com and Appannie.com to enhance the data retrieved from Apptrace.
•  Implemented a Python script to fuzzy match Developer & App information across iOS and Android apps.
Greater Los Angeles Area
https://media-exp1.licdn.com/dms/image/C560BAQERbXNaUkDd8A/company-logo_100_100/0/1612198729508?e=1655942400&v=beta&t=3wwrqASYEjOdsJ16A5TMOVmBTKNI1xF2LeE6Tx8UhIM
Graduate Research Assistant
Splunk
https://www.linkedin.com/company/splunk
Part of the Splunk4Good team as an application developer intern. Developed two apps leveraging open source data in the latest version of, Splunk Ember. 

• Created a Splunk app that informs about California's drought by depicting current status & trends in Groundwater levels, Reservoir levels, Urban water usage.
•  Implemented data retrieval and cleaning scripts using Python for the public data-sets. Contacted government departments to request data that was not easily accessible via APIs or dedicated data portals.
•  Developed the data model to ingest data from disparate sources in Splunk and represent a consolidated view thru Dashboards.
•  Modified the XML codes for visualizations contained in Dashboards, to enhance their functionalities beyond that offered by the standard GUI.
•  Conceptualized visual tokens that scaled down the data values for ease of understanding.
•  Collaborated to build a Splunk app to analyze San Francisco crime data (2007-2015) to find trends in criminal activity by correlating it with public holidays and sports events. 
• Identified strong correlations of decrease in crime on Christmas, 49er game days (regardless of the outcome) and increase (1.2-1.5 times average) in crime on New Year's eve.
•  Built end user visualizations and reports in Splunk allowing users to explore and find correlations as they see fit.
•  Participated in speaking to students about careers in Tech from high schools who visited Splunk. Was also a part of an intern event where we distributed emergency food packets, prepared by Meals on Wheels, to elderly and disabled individuals in Tenderloin area.
•  Won the Splunk4Good hackathon.
•  Completed Splunk Knowledge manager and Administration Certification tracks.
San Francisco Bay Area
https://media-exp1.licdn.com/dms/image/C560BAQFlJedtHL59Dw/company-logo_100_100/0/1594232691618?e=1655942400&v=beta&t=AjNQZAgT1uzk1vUJwv-Xl63pQCB5Le1_9RKZK-08r7o
Data Science Intern
Master of Science - MS
Informatics
https://media-exp1.licdn.com/dms/image/C4E0BAQHatTfEv4Af6w/company-logo_100_100/0/1519855864375?e=1655942400&v=beta&t=SJNQIMDMco5SIQwLeVARsdt5YDg6NO5m6sBOuWQd8Dg
University of Southern California
https://www.linkedin.com/school/university-of-southern-california/
Bachelor of Engineering (B.E.)
Core modules – 
Computer Programming I & II , Data Structures & Files ,Computer
organization & architecture, Database Management System, Analysis of Algorithm and
Design, Advance Database Management System, Data Warehouse & Mining, Robotics
& Artificial Intelligence, Systems Security, Distributed Operating systems,Computer vision,Software Architecture,Multimedia System Design
Computer Engineering
Mumbai Universtiy
H.S.C
Science
K.C College
I.C.S.E
Science
Christ Church School
A study on how new technologies will lead to a connected classroom and enhance the learning experience with the help of Multimedia content.
The future of Education and University Administration : A vision
International Conference on Eco-Friendly Technologies for Sustainable Growth, 2014
With the ever increasing number of automobiles in metro cities, there is an acute shortage of parking space to fulfill the demand. Moreover, paid parking facilities are charging hefty parking fees even for small durations due to their monopoly. In the proposed system we take a crowd sourced approach to identify free parking spots in streets and at curbs where the risk of the vehicle being towed away is minimum. These spots will be marked by the users and will be rated up or down to identify genuine and bogus spots. The system will also highlight nearby free alternatives to paid parking spots. This paper demonstrates the implementation of the GPS parking based system using Google API for locating the nearest free parking spot. Data mining performed on the request data received from the users will help us perform correlation analysis on interesting patterns in the most requested parking spots.
GPS Based Parking System for Unplanned Metrocities with Visualization of Request Data
International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 10
http://www.ijert.org/view.php?id=5864&title=gps-based-parking-system-for-unplanned-metrocities-with-visualization-of-request-data
A paper that illustrates the architecture and design of the project mentioned above. 
The paper also included the promising results we obtained when the system was compared to existing system.
Super Lightweight Inventory Management System
National Conference on Emerging Trends in Engineering
Received a Customer Excellence award for winning the first cybersecurity IDS mass production project globally with a major automaker. It represents one of the first IDS productions in the industry and created an entry point for Garrett to expand the business.
Garrett - Advancing Motion
Customer Excellence Award
Developed an app using public San Francisco crime data to find trends for certain types of criminal activity throughout different districts in San Francisco. Leveraged Splunk’s visualizations and custom UI capabilities for end users to find correlations as they see fit based on time, district, and/or type of crime.
Splunk Inc
Splunk4Good Hackathon
Graduated with a Bachelors degree  in Computer Engineering from University of Mumbai and was placed in First class with Distinction
University of Mumbai
First Class with Distinction
10950222
United States
10950222
Multimodal video system for generating a personality assessment of a user
https://patents.justia.com/inventor/aamir-k-goriawala
Analysis of Algorithms
CSCI 570
Applied Natural Language Processing
CSCI 544
Foundations and Applications of  Data Mining
INF 553
Foundations of Data Management
INF 551
Information Visualization
INF 554
Machine Learning for Data Informatics
INF 552
Overview of Data Informatics in Large Data Environments
INF 550
• Performed automated topic extraction from Amazon Product Reviews using Latent Dirichlet Allocation (LDA) and Non-negative Matrix Factorization (NMF).
• Analyzed performance of LDA over Non-negative Matrix factorization in extracting topics from a corpus, using 'perplexity', ‘word intrusion’ and ‘topic intrusion’ methods.
• Extracted topic-specific sentiment for individual aspect in a review using unsupervised polarity classifier from ‘usent’ library.

Languages used:
1. Python (Gensim and Scikit-learn)
2. R (tm and topicmodels package)
Topic Modeling and Topic-Specific Sentiment Analysis
•  Performed binary text classification on Enron emails dataset and IMDB movie reviews dataset using three machine learning techniques :- naive Bayes classification, maximum entropy modeling, and support vector machines.
•  Classified emails as SPAM or HAM (Not spam) and the reviews as POSITIVE or NEGATIVE. 
•  Implemented Naive Bayes model in Python with an accuracy of 84.82% in classifying sentiment and  95.71%  for Spam identification.
•  Leveraged MegaM and SVM Light tool-kits for sentiment analysis with an accuracy of  83.55% and 87.04% respectively
•  Obtained an accuracy of 95.84% and 98.52% for Spam identification using SVM Light and MegaM respectively.
• Language - Python
Text Classification using Machine Learning toolkits
•  Implemented data munging and cleaning operations using the pandas package in Python. 
•  Analyzed & identified relevant features from the dataset by using plotting functions from the 'matplotlib' library.
•  Modeled a random forest classifier using the Sci-kit learn package to predict the survival of passengers
Titanic - Machine Learning from Disaster
•  Implemented classifiers to recognize handwritten digits (0-9) from the MNIST dataset. 
•  Performed dimensionality reduction(data pre-processing) through principal component analysis to improve accuracy and runtime of k-Nearest Neighbors.
•  We achieved the best accuracy of 98.4% using the support vector machines, which was the best among our classifiers. 
•  We were able to consistently achieve an accuracy of more of 97% using the neural networks. 
•  Also implemented support vector machines and stochastic gradient descent. 
•  Ranked among top 100 teams in the Kaggle competition for digit recognizer.
•Language - Python
Classification of Handwritten Digits using MNIST dataset
• Devised and constructed an interactive visualization dashboard  leveraging D3.js.
• Project on ‘Substance Abuse among Youth’ with the aim of spreading awareness through interactive data visualization.
• Visualized federal government data, which previously existed in textual format to provide maximum insights.
• Statistical data made easy to understand through visual analysis.
• Users can view the data using multiple visualizations, providing an in-depth knowledge to a serious issue in our society.
• It depicts drug abuse trends from 2002-2013 in USA by drug type, age, state & informs about  adverse health effects of common drugs.
Interactive Data Visualization using D3.js
https://www.youtube.com/watch?v=LQQMBSnYCdA
•  Performed data cleaning on a real-world dataset using R. 
•  Used the results of the data cleaning process to train a classification algorithm (ID3), to predict the income class of a person on the basis of 11 attributes. 
•  The resulting decision tree had an 85.17% accuracy rate.
Prediction of Income Class based on US Census Data
•  A user-based collaborative filtering recommender system, which uses Pearson Correlation Coefficient find similar users to an active user and recommend movies to the active user based on movies that are highly rated by similar users. 
•  A weighted average of the similarity coefficient and users ratings are used to predict the ratings for unrated movies by active user.
Collaborative filtering recommender system
Obtained the Iris Flower Dataset from UCI Machine Learning Repository and implemented classification and clustering algorithms:
• Used the k-NN algorithm to classify the flowers using morphological features.
• Implemented k-Means clustering to identify clusters in the dataset.
Implementation of Clustering Algorithms
•  This project accesses the Twitter Application Programming Interface (API) using python to retrieve tweets which are stored as JSON objects.
•  The tweets are analyzed to estimate the public's perception (the sentiment) of a particular term or phrase and then we also calculate the frequency of terms in a twitter file.
Twitter Sentiment Analysis
An Android based crowdsourced system that provides information about free parking/paid spots in an area, to users from the data contributed by other users.The crowd-sourced data was mined to identify request patterns and areas that would benefit from dedicated parking infrastructure.  

Users can 
1. Tag free parking spots they know
2. Request for free parking spots in an area ( Can be the current location )

The nearest parking spots to the selected location are shown. 
These requests for parking spots are visualized using Data Mining Techniques to gain knowledge like which area's are most popular for parking, where do the most requests originate from, etc.

The system uses 
1. Google Maps API for tagging and displaying GPS coordinates.
2. OAuth for authentication
3. Google Fusion Tables for visualization

https://github.com/aamirg/WhereNot2Park-master
GPS based Parking System with Visualization of Request Data
https://github.com/aamirg/WhereNot2Park-master
An Inventory Management System targeted at the Micro - Small Business Segment.
These are the companies that do not need & can not afford full fledged Inventory Management systems that are available in the market and hence have to make use of manual techniques of book-keeping which are time-consuming as well as error-prone.

This software makes use of the web browser therefore it is:
1. Simple to interpret
2. Has a flat learning curve
3. Point and click (Minimal keyboard usage)

The key features of this software are :
1. Keeps track of the current stock of each item
2. Notifies the manager if the stock of a certain item has dropped below a certain threshold value.
3. Displays transactions according to Product, Customer, Supplier or Date range (which ever option is chosen by the user.)


https://github.com/aamirg/SuperLightweightInventoryManagementSystem-master/tree/master
Super Light Weight Inventory Management System (SLIMS)
https://github.com/aamirg/SuperLightweightInventoryManagementSystem-master/tree/master
Animal Welfare
Westside German Shepherd Rescue - Los Angeles
• Managing their RescueGroups.org platform, listing available animals for adoption.
• Managing Google Adwords account with an annual budget of $120k
• Participating in group training sessions for the shelter animals to teach them basic commands.
• Socializing and exercising the shelter animals.
• Awarded volunteer of the month for September 2016
Volunteer
Education
USC Viterbi School of Engineering
https://www.linkedin.com/company/usc-viterbi-school-of-engineering
Mentored two incoming international graduate students to help them transition successfully into a new academic environment. Shared my experiences, advised on courses to take, skills to develop and techniques to find on campus jobs, internships.
https://media-exp1.licdn.com/dms/image/C4D0BAQGLQ7K896s4aA/company-logo_100_100/0/1519907445001?e=1655942400&v=beta&t=U-0JYtS512f3R--mj6W7v8pD1gPC7yvdyYtl9Aaq9Tw
Graduate Mentor
Education
National federation of the blind, Maharashta
Was Actively involved in the fund-raising and converting English print books to Braille using software like Winbraille and Duxbury. Managed a team of 8 volunteers with whom I coordinated and distributed responsibilities equally to help in the conversion of academic texts to Braille for underprivileged students.
Volunteer
Tableau Software
www.youracclaim.com
Tableau Data Scientist
https://www.youracclaim.com/badges/cea9d09a-7fbe-447d-b7c0-b1f6b4372e0c/public_url
Coursera
www.coursera.org
Z5T925WJQ6FE
Convolutional Neural Networks
https://www.coursera.org/account/accomplishments/certificate/Z5T925WJQ6FE
Coursera
www.coursera.org
CNWJ3EW2YPKK
Structuring Machine Learning Projects
https://www.coursera.org/account/accomplishments/verify/CNWJ3EW2YPKK
Coursera
www.coursera.org
Y4N8VKEXL5VP
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
https://www.coursera.org/account/accomplishments/verify/Y4N8VKEXL5VP
Coursera
www.coursera.org
RHT83CUCHXDB
Neural Networks and Deep Learning
https://www.coursera.org/account/accomplishments/verify/RHT83CUCHXDB
Splunk
53696
Splunk Administration V.6
Splunk
49125
Knowledge Manager V.6
https://www.linkedin.com/in/rajansingh2
Solon, OH
Rajan Singh
Full Stack / AWS / DevOps Developer
https://www.linkedin.com/in/dustin-rohrer-18041b94
Raleigh, NC
Dustin Rohrer
Global Practice Manager, M&A and Divestitures at Bain & Company
https://www.linkedin.com/in/jasmine-wen
Durham, NC
Jasmine Wen
Duke University ‘23 | Economics, Statistics, Psychology
https://www.linkedin.com/in/anthony-sturdivant-338ab919
Raleigh-Durham-Chapel Hill Area
Anthony Sturdivant
IT Service Delivery Manager at Conduent
https://www.linkedin.com/in/davidzeitouni
Chapel Hill, NC
David Zeitouni
Senior Associate Consultant at Bain & Company
https://www.linkedin.com/in/alexa-campbell
New York, NY
Alexa Campbell
Senior Manager, Media at Bain & Company
https://rs.linkedin.com/in/ana-azanjac
Serbia
Ana Azanjac
Search Engine Optimization Manager at Gaming Innovation Group
https://www.linkedin.com/in/vaedk
Princeton, NJ
Vaed Khurjekar
Incoming Associate Consultant at Bain & Co.
https://www.linkedin.com/in/nico-shewey
Mercer Island, WA
Nico Shewey
Senior Technical Recruiter
https://www.linkedin.com/in/alanis-koberlein-171980118
Jacksonville, FL
Alanis Koberlein
Looking for new Opportunities
https://www.linkedin.com/in/gyc
Washington DC-Baltimore Area
Guanyu Chen
Data Science | Machine Learning | NLP | Certified AWS ML Specialist
https://www.linkedin.com/in/gkartikeya07
Bellevue, WA
Kartikeya Gupta
Azure Administrator Certified | Docker | Engineer-III at Ericsson
https://www.linkedin.com/in/stacystipes
Washington DC-Baltimore Area
Stacy Stipes
AWS Cloud Engineer | AWS Solutions Architect | 4x AWS Certified
https://www.linkedin.com/in/yuedeng0530
Fremont, CA
Yue Deng
Machine Learning Engineer at Cash App
https://www.linkedin.com/in/vasisht-raghavendra
San Francisco Bay Area
Vasisht Raghavendra
Imbibing Knowledge to Digital Assistants at Oracle
https://www.linkedin.com/in/muratyalcin-ai
San Francisco Bay Area
Murat Yalcin
Senior Data Scientist at Walmart Labs
https://www.linkedin.com/in/mezentsevpavel
New York City Metropolitan Area
Pavel Mezentsev
Senior Data Scientist
https://www.linkedin.com/in/mmahajan33
San Francisco Bay Area
Mayur Mahajan
Data Scientist at DoorDash
https://www.linkedin.com/in/maryam-imani
San Francisco Bay Area
Maryam Imani
Data Scientist at Walmart Labs
Yongzhi Wang
      
          



            
              
        
              
  

    
        Aamir is the best research assistants with whom I have worked. His work is efficient, professional, and organized. These are essential qualities for a data scientist. What should be valued more about Aamir is that he truly takes responsibilities especially when in situation of urgent tasks and that he takes initiatives in thinking ahead to make the work better. I would highly recommend Aamir because of his excellent performance while working with us as a research assistant in data management.
Liked by Aamir Goriawala
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Good morning. I am humbled to share that I joined MGM International yesterday as the Vice President of Data Science and Commercial Analytics, and…
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I've received countless comments and messages asking me to elaborate on my family's move to Rome, Italy.1. Why did we make this huge change?We…
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Developers are at the center of everything we do. We are making it easy for developers to learn security right when and where they need it. Proud to…
USC Engineers
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Computer & Software Engineering Professionals
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Viterbi Graduate Student Association (VGSA)
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Hadoop Professionals
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Entry Level Data Scientists
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Big Data and Analytics
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