An early childhood focus on Mathematics does wonders for a kid. In my opinion, there is no such thing as being bad at Mathematics. A strong base in Mathematics is directly correlated to Logic, Programming, Physics.
I prefer using a hands-on approach with my students, using examples both from school and outside of school materials. My teaching method, approach, tricks were all picked up through my education in Singapore, a world-class country for Mathematics.
I am currently a Senior Data Scientist with a leading Technology company. I have a degree in Statistics with an added focus on Statistical Modeling. I have worked in Consulting and Academia prior to this.
I had my early schooling in Singapore before coming to Austin, Texas for college.
I have tutored kids both in Singapore and the US in various Mathematical topics.
I mentor young Data Scientists to help them navigate their journeys.
Dell – Data Scientist; Austin, Texas July 2018 – Present
● Select features, building and optimizing classifiers using various machine learning techniques in R, Python
● Expertise in Statistics, Validation of statistical models, and the development of forecasting models to include time series and curve fitting
o Presented predictive analytics for sales hiring to C-Level executives. Explained SVM, K-means, and Regression algorithms to team. Resulted in a more tuned in Talent Acquisition process
● Implemented NLP algorithms for Sentiment Analysis and Topic Modeling for the Dell IT team.
o Used SVM and Naïve Bayes’ Classifiers to automate polarity score reporting, increasing efficiency by 400%
● Full-Stack development of compensation-focused machine learning application deployed in R Shiny
o Utilized NLP for job matching, cluster analysis for country scorecard matching, and Gradient boosting to output predicted market price.
● Created a Diversity and Inclusion time-series forecasting model to drive policies to meet internal Dell 2030 targets
● Dash-boarding and Data Visualization in Tableau, ad-hoc analysis, and presenting results in slide decks
● Work with HR and Finance teams to create automated anomaly detection systems and track performances.
o Created a Best vs Rest dashboard for allocation of resources
● Project Management with JIRA in Scrum/Agile environment
Integra FEC LLC – Quantitative Research Analyst; Austin, Texas August 2017 – July 2018
● Conduct research to understand and identify manipulation, market-rigging, credit ratings, mortgage fraud, misrepresentation of asset backed securities and healthcare fraud
o Using Outlier Analysis, Discovered and investigated anomalous behavior of structured products in a misrepresentation case involving a top international bank in San Francisco
● Clean, compile, analyze, and visualize structured and unstructured datasets in R, Python, and PostgreSQL
o Interfaced with distinguished academics all over the world by working on projects, papers that demanded heat maps, trends, hypotheses using R Markdown and Jupyter Notebook
● Conduct exploratory data analysis/data visualization followed by feature selection for data science applications
o Identified 8-10 additional lead underwriters on top a list provided by the SEC that engaged in Municipal Bond trading fraud using Machine Learning Algorithms
● Produce reproducible dashboards and present findings to the team, clients, and members of the SEC and DOJ
The University of Texas at Austin - Data Science Research Assistant; Austin, Texas August 2016 - May 2017
● Utilized Machine Learning (ML) tools and libraries to conclude that Risk-Reducing Salpingectomy was a significant predictor of operative time of Cesarean Sections
o Built Databases, Schemas, and Tables to query, organize and manage various cross sections of over 10 GB of unstructured data collected from numerous surgical procedures
o Cleaned data using linear interpolation, cosine interpolation, and mean imputation, to overall positive impact when compared to a test case where data was manually deleted to check for accuracy of imputed values
● Regression, Statistical Analysis, ANOVA, and Dash boarding
o Used R Studio to build logistic, multinomial, multiple, simple, mediated regression models
The methods measured significance of various predictors, interactive effects between variables, more than two possible discrete outcomes, and identified the existence of a mediator variable
o Designed and generated reproducible, client-friendly dashboards using R Markdown, and knit function
The University of Texas, Austin May 2017
Bachelors of Science, Mathematics, Specialization in Statistics, Probability and Data Analysis
Certification in Statistical Modeling
Major GPA: 3.7
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