Aakriti Kaul
Data Scientist at BCG GAMMA
Data Scientist at BCG GAMMA
BCG GAMMA
https://www.linkedin.com/company/bcg-gamma
Aligned with BCG Gamma as a data science consultant to:
- Work with client teams on AI/Advanced algorithms and power custom solutions
- Design and build analytics solutions for data intensive client requirements 
- Leverage statistical methods and objective research to support recommendations
Los Angeles, California
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Data Scientist
University of California, Berkeley
https://www.linkedin.com/company/uc-berkeley
Module lead for Natural Language Processing and ArtificiaI Intelligence as it pertains to human cognition
College of Letters & Science
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Graduate Student Instructor - Cognitive Science
BCG GAMMA
https://www.linkedin.com/company/bcg-gamma
Greater Los Angeles Area
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Summer Analytics Associate
University of California, Berkeley
https://www.linkedin.com/company/uc-berkeley
- Research intern on a Social Science Matrix project to transform raw government documents into databases that can be easily accessed and queried by researchers and the public 
- Co-authored Jupyter notebook tutorials guiding future researchers and digital librarians through the process of creating such document databases
- Mentored undergraduate students from URAP (Undergraduate Research Apprentice Program) on testing the tutorials through a semester long course
Berkeley Institute for Data Science (BIDS); Goodly Labs
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Research Assistant - Computational Text Analysis (Berkeley Social Science Matrix)
Deloitte
https://www.linkedin.com/company/deloitte
Mumbai
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Business Technology Analyst
Master of Information Management and Systems
Data Science & Analytics
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UC Berkeley School of Information
https://www.linkedin.com/school/uc-berkeley-school-of-information/
Bachelor of Engineering
Information Technology
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Savitribai Phule Pune University
https://www.linkedin.com/school/university-of-pune/
Science
Lilavatibai Podar High School
Deloitte
Business Technology Analyst
Computer Society of India
Student Member
IEEE
Student Member
Recognized for ownership and contribution to a global LSHC project by integrating GridBuddy solutions
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Spot Award
Commended for successful work on client service for a C&IP giant within USA while at Deloitte USI
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Applause Award
Received accolades for promising work on an internal firm initiative while at Deloitte USI
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Spot Award
YMCA,Mumbai
BRAINWAVES Young Writers
Awarded certificate for stellar performance in the annual Achievement and Aptitude Test – AAT
Lilavatibai Podar High School
Outstanding Performance AAT
Awarded medals and certificates for being part of the school Track Team across four years
Lilavatibai Podar High School
Proficiency in Sports
Applications In Data Analysis
INDENG 242
Artificial Intelligence
CS 188
Data Mining & Analytics
INFO 254
Database Management
INFO 257
Information Law and Policy
INFO 205
Information Visualization and Presentation
INFO 247
Introduction to Statistical Computing
STAT 243
Natural Language Processing
INFO 259
Quantitative Research Methods for Information Systems and Management
INFO 271B
Social Issues of Information
INFO 203
Object Oriented Modeling and Design
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Theory of Computation
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U.S politics have gained global traction, with conversations about policy changes, voting rights and impact on voting behavior. Past research examines what may factor into costs, and political geography is one such component. As behavioral economists have stressed multiple times, human beings are not rational actors, which begs the question - how does this reflect in voting behaviors? 

Our ongoing research aims to understand the impact of polling place closures on voter turnout and more broadly, how does that inform the future of electoral ergonomics? Our current method works towards measuring the effect of polling place changes using a novel geographical regression discontinuity design, based on granular voter locations
The Effect of Moving Polling Places on Voting
Applied data mining and analysis techniques to understand engagement metrics on YouTube's "popular" videos leading with the research question:

Are metrics such as comment ratio and like ratio a function of the relationship between title and description of a video? To what extent does “clickbaitiness” affect engagement?
To Click or Not To Click: YouTube Engagement Analysis
Leveraged R for descriptive and predictive analysis for a major utility company to classify customers' churn propensity and to provide data-driven strategies for their retention marketing campaign
Customer Churn Analysis
Developed a complete R package to implement a genetic algorithm for variable selection in regression problems, including both linear regression and GLMs.
Genetic Algorithm Package
Leveraged Python to build a supervised machine learning model and gain insights about the distribution of Ekman's Six Emotions in a 'parent tweet - reply tweets' hierarchical structure for polarizing entities
Hierarchical Opinion Mining in Twitter
Developed running implementations of information organization and retrieval concepts- semantic representation, conceptual modeling, metadata design and classification using Python.

Implemented the retrieval system to serve a two-fold purpose:
- Provide a regular, attribute based search engine to new or existing users
- Provide an enhanced, personalized recommendation system for returning users
Yelp Help: Personalized Recommendation System for Yelp Users
Performed exploratory data analysis to derive a correlation between the total acquisition cost incurred (TAC) for USA's "Excess Property Program" and the impact of these on criminal activity and law enforcement in different states

- Created a multi panel line plot to find comprehensive trend lines wherein the most evident observation made is the relation of crime rate to the number of law enforcement agencies
- Created map components to study the trend across states and used color encoding that shows the prominence of the major variables in all the states. Multiple maps are compared to see if there is a correlation between variables
Excess Property Program - Effectiveness for Law Enforcement
http://aakritik.github.io/US-State-Arms/
Performed analysis to to understand the trend of venture capital investments in multiple forays of the country for Clean Technology and Corporate Technology

- Created a themed plot to show a linear chart of investments made to each technology over the years right from the year 1995. A significant observation was made of a lull in investment during early 2000s towards both sectors. This could be attributed to the decline in economic activity which mainly occurred in developed countries during that period
- Converted data from the regional venture capital investments into a Time Series format to analyze the data across time and across regions.
- The Time Series plot is generated for total venture capital investments by region from 1985-2014 with color encoding for each region. Silicon Valley has, predictably, the highest investments made into technology across spheres consistently
Investing in Genius - Venture Capital Investment Analysis
http://aakritik.github.io/Venture-Capital-Data/
Used R programming techniques to generate a plot for mapping trend of duration of storms across specific set of start dates

- Created a multi panel line plot to find comprehensive trend lines for intensities of their sustained winds during storms across each month. The data is color encoded per the ratings on a standard Saffir Simpson scale, used for classifying hurricanes
- Implemented a bar plot to portray count of each category storm - hurricane, cyclone, super typhoon, tropical depression, tropical storm, typhoon - across the six major storm afflicted regions
- Additionally implemented a comparative plot of names given to each recorded storm to analyze naming trends across the six major storm afflicted regions. Both male and female names are equally distributed, however gender-neutral names are most commonly used for official records and data
Storm Trooper
http://aakritik.github.io/Storm-Trooper/
The project analyses data from the ill-fated maiden voyage of the RMS Titanic
Through a visualization created in Tableau we can understand the impact of different parameters - age,economic status, gender - on the survival rate of an individual onboard the liner

- Color encoding throughout the visualization is used to depict the survivors - marked as blue - and those who did not survive, marked in red
- Through the drop down menus provided, the user can further study the fate of a specific group of individuals, based on sex. This categorical data is also depicted through classic symbols of gender
- Trend lines plotted for correlation between survivor count and age debunk the "women and children first" belief
- It is observed through the use of an interactive bubble chart,the higher the economic status the better the chances of survival. A large percentage of survivors were passengers from the 1st Class aboard the ship
- Through a tool tip we get more detailed and compact information which can help us summarize the learnings from provided data
The Tragedy of RMS Titanic - Data Viz for Survival Analysis
https://public.tableau.com/profile/aakriti.kaul#!/vizhome/TitanicATragedy/TheTragedyofTheTitanic
Performed analysis to visualize what respondents in 40 countries thought about eight topics often discussed as moral issues

- The visualization uses a global map view to mark each of the 40 countries where the survey was conducted. Hovering over each marker provides a summary of results from the country and the percentage of total responses provided from one of ten geographical regions
- The map view also implements a zoom and drag feature which in turn enables the user to zoom into a specific country or drag a specific country into view
- Implemented multiple drop down menus for easy filtering of data
- Created three interactive charts which enlist each response to a morality issue in individual columns. Thus, a matrix of country-response-topic is formed for easy interpretation of data. The chart data modifies per selection of markers on the global map component and vice versa
Global Morality Compass - A Data Analysis Implementation
https://public.tableau.com/profile/aakriti.kaul#!/vizhome/GlobalMoralityScale/AGlobalView
Analysis of data on winners of the Golden Boot award in football, particularly within the English Premier League. The viz allows manipulation of parameters such as Club name,nationality of player and minimum goals

- Created a Tableau dashboard to visualize the statistics of players in the English Premier League who have won the Golden Boot award
- Enables the user to analyze the performance of players to find out the top players and their winning season, impact on the club they belong to and total goals scored
- Players from different nationalities are color encoded to compare performance of different players or to compare within one nationality
- Through parameter control, the number of minimum goals scored can be changed to produce detailed information about a specific group of players
- Size of the bubbles helps us differentiate between players with different number of goals
- By leveraging a tool tip the user can obtain more information about a specific player
- The highlighting feature is active which enables the user to selectively view only a specific set of players in order to delve deep into the analysis
Data Analysis for Premier League Golden Boot Winners
https://public.tableau.com/profile/aakriti.kaul#!/vizhome/PremierLeagueGoldenBootWinnersAnalysis/GoldenBootWinners-PremierLeague
Project Objectives:
- To design and implement a Content Based Image Retrieval System using HSV color model
 - Make use of Canny Edge Detection Algorithm along with the HSV algorithm to get accurate results
 - Use K-means algorithm for creating clusters of images from the database.

The project was developed using Core Java and the IDE development in Eclipse. Apache Tomcat Server was used for client and server ends.
Content Based Image Retrieval Using HSV Color Model
Project Management System is a prototype Windows based application to manage engineering mini projects for a specific program. It can be extended to include data for an entire school or university.
- The solution provides a customized system for collection and documentation of present and past projects :
• supports multiple projects,
• allows uploads of documents
• contains activity tracker
• allows quick searches on the basis of academic year or project supervisor

- Developed using Visual Basic for front end design and data manipulation through PL/SQL which interacts with the database at the back end
- Followed Rapid Application Development as the engineering model
Project Management System - A Database Management Project
Salesforce
2637088
Salesforce Certified Force.Com Developer
https://www.linkedin.com/in/ramanadeepsingh
Los Angeles, CA
Raman Deep Singh
Data Scientist at BCG GAMMA
https://www.linkedin.com/in/deng-hua
Los Angeles, CA
Hua Deng
Data Scientist @ BCG GAMMA | M.S. in Business Analytics @ UCLA Anderson
https://www.linkedin.com/in/dominicbreuer
Boston, MA
Dominic J. Breuer
Senior Data Scientist at Boston Consulting Group (BCG)
https://www.linkedin.com/in/wenxi-lei-6998b68b
Los Angeles Metropolitan Area
Wenxi Lei
Lead Data Scientist at BCG GAMMA
https://www.linkedin.com/in/charles-herrmann
Greater Boston
Charles Herrmann
Data Scientist at BCG GAMMA
https://es.linkedin.com/in/roberto-kramer-8b970974
Madrid
Roberto Kramer
Senior Data Scientist
https://www.linkedin.com/in/arthur-pentecoste
New York, NY
Arthur Pentecoste
Data Scientist at BCG GAMMA
https://www.linkedin.com/in/-lu-sun
Cambridge, MA
Lu Sun
Senior Data Scientist at BCG GAMMA
https://www.linkedin.com/in/abby-ruixue-gong-aab0775b
Boston, MA
Abby (Ruixue) Gong
Consultant & Data Scientist at Boston Consulting Group (BCG)
https://www.linkedin.com/in/alessandro-scaglia
New York, NY
Alessandro Mario Scaglia
Data Scientist at BCG GAMMA
https://www.linkedin.com/in/jeffreyzhaojy
Los Angeles, CA
Jiyuan (Jeffrey) Zhao
Data Science at Wish | ex-BCG, ex-Uber
https://www.linkedin.com/in/swathysujit
Greater Chicago Area
Swathy Sujit
Data Scientist at Boston Consulting Group (BCG) | MS in Analytics at UChicago
https://www.linkedin.com/in/liangliang-dylan-huang
New York, NY
Liangliang (Dylan) Huang
Data Scientist at Two Sigma(TSIQ) | ex-BCG | Columbia
https://www.linkedin.com/in/jerrizhang1
Boston, MA
Jerri Zhang
Data Scientist at Boston Consulting Group (BCG)
https://www.linkedin.com/in/sachdevakunal
Chicago, IL
Kunal Sachdeva
Consultant / Senior Data Scientist at BCG | Georgia Tech | IIT
https://www.linkedin.com/in/wangjingke
San Francisco Bay Area
Wangjing (Jing) Ke
Lead Data Scientist | Project Leader at The Boston Consulting Group (BCG), BCG Gamma
https://www.linkedin.com/in/skand-upmanyu
New York, NY
Skand Upmanyu
Data Scientist at BCG GAMMA
https://www.linkedin.com/in/weizouserena
San Francisco Bay Area
Wei (Serena) Zou
Data Scientist at The Boston Consulting Group (BCG)
https://www.linkedin.com/in/hunkartoyoglu
Dallas-Fort Worth Metroplex
Hunkar Toyoglu
Associate Director Data Science at BCG GAMMA
https://www.linkedin.com/in/akaragou
New York, NY
Andreas K.
Data Scientist at Accenture
Ajay Agnihotri
      
          



            
              
        
              
  

    
        "Aakriti would be an asset to any team."

As a team member she was always organized, Planned & Interactive, she has good blend of technical and functional aspects. She is a person who is always ready to take challenging roles with complete ownership.

Apart from her technical abilities , she also have great communication skills which always adds to her persona, It was a great pleasure working with her, and would like to recommend her for her future roles.
 Pankaj Banik
      
          



            
              
        
              
  

    
        Aakriti is a hardworking, astute and quick learner. As a senior in her team, I have seen her pick up and implement new things quickly. She has a sharp mind, and quickly understand business scenarios and how to translate it to technical implementations. She is a team worker always ready to help out her teammates. 
https://in.linkedin.com/in/aakriti-kaul-86ab0493
Delhi, India
Aakriti Kaul
Edtech
https://in.linkedin.com/in/kaulaakriti
Bengaluru
Aakriti Kaul
MBA | Content | Digital
https://ca.linkedin.com/in/-aakritikaul-
Ottawa, ON
Aakriti Kaul
Architect | BIM Enthusiast | Project Management student | Captain at MPWR
https://in.linkedin.com/in/aakriti-kaul-5a19451a4
New Delhi
Aakriti Kaul
Senior Consultant at EY || IT Audit || Technology Risk Consulting || SCIT 2016