aaditya bhat
Senior Data Engineer at Robinhood
data @ robinhood
data science professional extensive experience data engineering , analytics data modeling . year , worked diverse industry tech , healthcare , finance , mobile analytics manufacturing . currently , working data engineer news feed facebook . portfolio website - aadityabhat.com
Robinhood
https://www.linkedin.com/company/robinhood
New York, New York, United States
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Senior Data Engineer
Facebook
https://www.linkedin.com/company/facebook
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Data Engineer
Cohen Veterans Network
https://www.linkedin.com/company/cohenveterans
Stamford, Connecticut
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Vice President, Data Science
Cohen Veterans Network
https://www.linkedin.com/company/cohenveterans
Data Infrastructure 
- Designed a multi-fact Data Warehouse using Star schema design principles. Incorporated Slowly Changing Dimensions, Junk dimensions, Smart-keys, Degenerate dimensions in the design. Deployed the data warehouse on managed PostgreSQL instance in Azure. 
- Created ETL pipelines using Pentaho, Python to load the data warehouse incrementally. Scheduled ETL jobs using batch jobs and Windows Task Scheduler.
- Implemented a code repository to organize and manage code. Established coding guidelines, style guide and code review process to improve the code quality.
- Created a Python module to consolidate and modularize common data manipulations,  analytical and plotting functions. The Python module streamlined the exploratory analysis reducing the development time by 30%.
- Created a reporting framework using IPython, papermill, and wkhtmltopdf. Produced reports using the framework to replace the existing SPSS, Excel, and Word reports. The new framework reduced the report generation time by 80%, and eliminated manual errors.

Data Modeling  
- Created various ad-hoc analyses and reports to support Senior leadership, C Suite and Board of directors.
- Performed Hypothesis testing to quantify how Clients were getting better after completing the course of treatment.
- Created a model to predict treatment drop-offs using Logistic Regression algorithm. Collaborating with Research and Clinical Programs departments to implement this model in clinics.
Designed reports to assist Clinical Programs department to pilot Continuous Quality Improvement (CQI) process. CQI Reports enabled Clinical Programs to monitor various indicators related to Clinic’s overall health.
Stamford, Connecticut
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Data Scientist
Apptopia
https://www.linkedin.com/company/apptopia
•	Created a model to predict 30-day Customer Retention for apps using Random Forests algorithm. Assisted engineering team to deploy the model in the production environment.
•	Created App Graph, a network with Apps as nodes and common Users as edges. Calculated Jaccard Index to quantify the common audience in more than 2 million app pairs. 
 •	Created keyword report in Spark to find specific keywords in app reviews. Applied text mining techniques such as stemming, stop word filtering to improve the accuracy of the report. 
•	Analyzed the effects of Snapchat’s ‘In App Purchase’ option on its performance in iTunes and Google Play.
•	Identified advertising opportunities in Pinterest customer base by analyzing Pinterest demographics data.
Greater Boston Area
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Data Scientist
GMO
https://www.linkedin.com/company/gmo
Data Warehousing -

•	Contributed in the design of a new data mart for Compliance Reporting. Implemented principles of Star Schema, Slowly Changing Dimensions, Junk Dimensions, Smart Keys in the design.
•	Created an ETL (Extract, Transform, Load) workflow in Pentaho to load the Compliance data mart from source systems. This improved data consistency and reduced maintenance efforts for Compliance Reporting. 
•	Added logging functionality to existing import/export stored procedures, improving data governance.

Business Intelligence - 

•	Converted existing static reports to interactive QlikView dashboards. Created new reports to cater the data needs of business users.
•	Proposed incremental data loading for QlikView applications. Incremental loading significantly reduced the daily reload time for QlikView applications.
•	Automated deployments for QlikView projects using QlikView API, C#, and Powershell. This achieved near real-time data on QlikView applications.
•	Evaluated a third party tool, ‘QV Source’ for connecting QlikView to SOAP API’s. Created a POC (Proof of Concept) and presented it to the management.

Static Reporting - 

•	Created static reports in eReportal for Trading teams. Automated the delivery of these reports using Cisco Tidal Enterprise Scheduler.
•	Analyzed the usage patterns for existing reports, compiled a list of unused reports to be retired.
•	Created custom controls in ASP.NET MVC framework to complement static reporting application. These custom controls made the UI more user-friendly and intuitive for end users.
Greater Boston Area
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Reporting/ Business Intelligence Developer Co-op
Northeastern University
https://www.linkedin.com/company/northeastern-university
Graduate Teaching Assistant for 'Data management and database design' under prof. Mutsalklisana.
• Taught Normalization, Joins, Indexes to the class.
• Advised 3 teams of 5 students for their course project.
• Conducted TA sessions for students and graded their homework.
Greater Boston Area
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Graduate Teaching Assistant
TransparencyX LLC
• Designed and implemented an Operational Database in MySQL to store the Merchant Statements. The database was normalized to 3NF, to minimize storage and maximize write performance.
• Written a Python script to parse Merchant Statement PDF's and store it in the database.
• Created a 'Fee Calculator' in Python, to calculate fee for a transaction given various parameters of the transaction.
Greater Boston Area
Database Developer Intern
Vesat Plastics
•	Analyzed demand and production data to forecast monthly sales and revenue. The forecast was used to plan cash flow.
•	Planned and supervised installation of a new injection molding machine which resulted in increased production capacity by 15%
•	Implemented a semi-automated sealing process replacing the conventional manual sealing. Achieved  reduction in the sealing time by 25%
•	Optimized injection molding parameters such as cooling time, mold pressure, injection pressure, ejector pressure. Thus, reducing the production time by 10% while maintaining acceptable quality standards. 
•	Handled a complaint from a client about warpage problem in one of the products. Eliminated the problem by redesigning the product, and changing the molding parameters for the product.
Vasai, India
Partner
Master’s Degree
Engineering/Industrial Management
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Northeastern University
https://www.linkedin.com/school/northeastern-university/
Bachelor's Degree
Automobile Engineering
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University of Mumbai
https://www.linkedin.com/school/university-of-mumbai/
Panel Discussion: Advancing Mental Healthcare using Data Science
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Panelist at Cohen Veterans Care Summit 2018
Northeastern University
Academic Excellence Award
Big-Data System Engineering using Scala
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Concepts of Object Oriented Design - JAVA
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Data Management and Database Design
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Data Warehousing & Business Intelligence
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Deterministic Operations Research
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Economic Decision Making
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Engineering Probability and Statistics
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Engineering Project Management
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Data Scientist's Toolbox
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Developing Data Products
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Exploratory Data Analysis
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Getting and Cleaning Data
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Practical Machine Learning
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R Programming
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Regression Models
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Reproducible Research
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Statistical Inference
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iPython Notebooks for Probability & Statistics
https://github.com/aadityaubhat/ProbAndStats
Built a reactive Web App which predicts the next word based on the entered words.
Word Prediction
https://aadityaubhat.shinyapps.io/app_word_prediction/
•	Build a recommender engine using Zeppelin and Scala to recommend products to existing customers according to their current products and profile.
•	Analyzed 13,647,309 rows and 50 columns of historic customer data, to perform exploratory analysis and discover patterns in the data. 
•	Performed data transformation using Spark and Scala.
•	Evaluated various learning algorithms using MLlib in Spark. Selected Random Forests Algorithm with Mean Average Precision of 0.025.
Santander Product Recommendation
https://github.com/aadityaubhat/CSYE7200
•	Examined the correlation between Controversy and Number of Views for YouTube videos.
•	Parsed data for 426 videos in 16 categories using YouTube Data API.
•	'Autos & Vehicles', 'Entertainment', 'Pets & Animals', 'Sports' and 'Travel & Events' had a statistically significant positive correlation between Controversy and Number of Views.
•	'Travel & Events' category had the strongest positive correlation with  Correlation Coefficient of 0.50 and P- value for non correlation of 0.56%
YouTube Data Analysis
http://aadityaubhat.github.io/youtubeAnalysis/
•	Created a data warehouse for a fictional company called 'Contoso Retail' in MS SQL Server of size 5.8 GB
•	Implemented Error Handling, Load Statistics, Slowly Changing Dimensions, and Currency Conversion for Data Integration process using Talend 6.1 and SSIS.
•	Used bulk output connections instead of standard output connections to reduce the data integration duration by 80%.
•	Built Business Intelligence Dashboards using Tableau, QlikView, and Excel PowerPivot.
Data Warehouse and Business Intelligence for Contoso Retail
•	Analyzed 'Motor Trend Road Tests'​ data to determine whether automatic or manual transmission is better for MPG.
•	Performed a Welch's T test to check whether type of transmission affects MPG. The null hypothesis had p- value of 0.001374, indicating that there existed a significant difference between average MPG for Automatic and Manual transmission.
•	Fitted a multivariate Regression Model to explain the variability in MPG with respect to other variables. The model had an R - squared value of 0.8659. Hence explaining 86.6% variability in MPG.
•	The analysis concluded that Manual Transmission results in an increase of 1.81 MPG.
Analysis of 'Motor Trend Car Road Tests' dataset
http://aadityaubhat.github.io/regression_models/
•	Deployed a Shiny App to predict the stopping distance given the speed of the car.
•	Used 'cars' dataset in the R to fit a linear regression model.
•	The model had an R squared value of 0.8963 and P-value of 2.2e-16.
Stopping Distance Prediction App
https://aadityaubhat.shinyapps.io/dist_prediction_app
•	Created a prediction model to predict the manner in which the participants did the weight lifting exercise.
•	The prediction model was build using a training dataset of 19,622 observations of 160 variables. The training dataset was split into two sets, 'Training'​  & 'Validation' to predict the out of sample error.
•	The final model consisted of ‘Random forests’ algorithm with 52 predictors.
•	Accuracy of 99.88% along with p-value of 2.2e-16 was achieved.
Weight Lifting Exercise Prediction Model
http://aadityaubhat.github.io/pml_project/
•	Created a Relational-Database to study and predict the spread of Ebola Virus Disease, using MySQL.
•	Denormalized the model and added various indexes to improve the query response time. Query response time was reduced by more than 50%.
•	Generated test data for 1000 reported cases, using R and MS-Excel.
•	Data was used to test various database objects, such as Stored Procedures, Triggers, Views, Indexes, etc.
•	Created various users & assigned them privileges to improve the security of the database.
•	Proposed a backup schedule.
Database to study and predict the spread of Ebola
Coursera
www.coursera.org
ZATCP2USDG3E
TensorFlow in Practice
https://www.coursera.org/account/accomplishments/specialization/ZATCP2USDG3E
Coursera
www.coursera.org
SJAF88UC8B8F
Data Science Specialization
https://www.coursera.org/account/accomplishments/specialization/SJAF88UC8B8F
Coursera
www.coursera.org
K8CC358NYYT6
Functional Programming Principles in Scala
https://www.coursera.org/account/accomplishments/verify/K8CC358NYYT6
Coursera
www.coursera.org
CN8MCEA6PY3K
Machine Learning
https://www.coursera.org/account/accomplishments/certificate/CN8MCEA6PY3K
https://www.linkedin.com/in/simran-modi
San Francisco Bay Area
Simran Modi
Data Engineer 2 at Meta
https://www.linkedin.com/in/this-is-ankit
Seattle, WA
Ankit Sharma
Senior Software Engineer at Robinhood
https://www.linkedin.com/in/aashna91
San Francisco, CA
Aashna .
Engineering Manager at Robinhood - We're Hiring
https://www.linkedin.com/in/jay-pandya-b5b65330
San Francisco Bay Area
Jay Pandya
Software Engineer at Robinhood
https://www.linkedin.com/in/mohitbhura
Palo Alto, CA
Mohit Bhura
Senior Software Engineer at Robinhood
https://www.linkedin.com/in/msaxena123
San Francisco Bay Area
Mayur Saxena
Engineering Manager @ Robinhood
https://www.linkedin.com/in/kwan-i-lee-91212248
San Mateo, CA
Kwan-I Lee
Staff Software Engineer at Robinhood
https://www.linkedin.com/in/amy-werner-allen-data-science
Greater Seattle Area
Amy Werner-Allen
Data Science Manager at Facebook
https://www.linkedin.com/in/sujithktkm
Santa Clara, CA
Sujith Katakam
Senior Software Engineer at Robinhood
https://ca.linkedin.com/in/rogerding8868
Toronto, ON
Roger (Chao) Ding
Data Scientist
https://www.linkedin.com/in/siddparkar
Kansas City Metropolitan Area
Siddhant Parkar
Software Engineer II at Cerner Corporation
https://www.linkedin.com/in/jose-cueva-8072a546
New York City Metropolitan Area
Jose Cueva
Co-Founder at Tenna
https://in.linkedin.com/in/sagir-shaikh-4089b779
Pune
Sagir Shaikh
Assistant Manager |MAN Truck & Bus|Ex- Scania CV AB|
https://www.linkedin.com/in/dikshathakur3119
San Francisco Bay Area
Diksha Thakur
Software Engineer at Google
https://in.linkedin.com/in/apoorva-sharma-9a9620155
New Delhi
Apoorva Sharma
Software Developer Engineer 3 at Walmart Global Tech
https://www.linkedin.com/in/athiradas
San Francisco, CA
Athira Das
Senior Data Engineer @ Instagram
https://www.linkedin.com/in/deeppatel710
San Francisco Bay Area
Deep Patel
Data @ Robinhood
https://www.linkedin.com/in/tejalnarkar
San Francisco, CA
Tejal Narkar
Senior Data Engineer at Facebook
Allison J Palombo (she/her)
      
          



            
              
        
              
  

    
        Aaditya and I worked together for only a short amount of time at Apptopia, but during that time I was always impressed by his professionalism, dedication to his work and overall positive demeanor in office.  He is an asset to any team he is a part of.  John Mercer
      
          



            
              
        
              
  

    
        I was proud to have recruited Aaditya to my team and train him as we transformed Apptopia into a major player in mobile intelligence. Aadiya, or as I nick-named him "A-game", is a talented engineer, data analyst, and modeler. He was diligent, hard-working and professional. He made solid contributions to the team and our platform and I'm sure he will have a great career. 
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We can't wait to see #CVNTogether next week in Fort Worth, TX! For the first time since 2019, staff from around Cohen Veterans Network will come…
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I am excited to announce our $10mn round led by Unusual Ventures, with participation from HubSpot Ventures, Afore Capital and Underscore VC…
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🏆 4:30PM TODAY! Which 🍎 NY🗽team will represent NY/Northeast USA in the Alumni NVC 🌎 Globals ➡️ @ Harvard Business School in March?…
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Mumbai
Aaditya Bhat
Student at Indian Institute of Technology, Bombay
https://in.linkedin.com/in/aaditya-bhat-2aa0a1128
Bengaluru
Aaditya Bhat
System Administrator at Vee Technologies
https://in.linkedin.com/in/aaditya-bhat-58b4b2218
Pahalgam
AADITYA BHAT
Student at University of Mumbai
https://in.linkedin.com/in/aaditya-bhat-61535b18a
Jammu & Kashmir, India
Aaditya Bhat
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KDnuggets AI, Big Data, Data Science, Machine Learning group
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Data Science, Deep Learning, and AI
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Artificial Intelligence and Business Analytics (AIBA) Group
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Northeastern University Employer Engagement and Career Design
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Python Professionals
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