Howdy! Thanks for visiting my page. I'm Moorissa, but more often go by Sasa. I was born and raised in Malang, a small city in Indonesia known for its apples and active volcanoes hikes. As adventurous as my hometown made me to be, I've started living on my own when I was 13. I have since traveled to more than twenty countries worldwide (though New York City and Interlaken are still my favorite place to date).
I moved to the United States as a Shannon and Wilson scholar six years ago. Three and a half years later, I graduated from Georgia Tech and subsequently worked as a data analyst for the next two years until my arrival at Columbia. Loving my first full-time job, I decided to pursue data for my long-term career.
My expertise and interests include machine learning, predictive modeling, data visualizations, business intelligence, and cross-functional teamwork. I also get really excited when it comes to data for good. One of my favorite highlights this past fall was winning the 2016 Impact Hackathon by Columbia Business School.
When I'm not playing with data, I enjoy learning new things, spending quality time with loved ones, and constantly thinking about ways to change the world.
B.S. in Industrial Engineering, c. Statistics and Quality• May '14
GPA: 3.8 / 4.0 (Summa Cum Laude)
Relevant Coursework: Probability Theory, Statistical Inference and Modeling, Database Systems Design and Manipulation, Regression and Forecasting, Quality Control, Optimization, Reliability Engineering (graduate level), Stochastic and Queueing Theory.
Data Analyst • Jul '14 - Jun '16
Managed data warehouses, built statistical models, developed interactive decision support tools. Selected as lead analyst for three accounts in < 2 years. Collaborated closely with Senior VP of Analytics and Head of Analytics in integrating strategy execution, methodologies, risk and analytics.
Logistics and Modeling Engineer • Oct '13 - May '14
Developed a user interface for inventory optimizations, yielding an annual savings of $1.02M and 30% increase in the profit margin of the consumables business. Performed simulations, time series analysis, forecasting, and stochastic mixed integer programming to optimize distribution channels.
Research Assistant • Aug '13 - May '14
Constructed a multivariate hub model for Specialized Nutritious Foods with Dr. Nazzal and Spatial Risk Calendar (SPARC) team at WFP. Resulted in 30% decrease in malnutrition rates + commodity shortages across sub-Saharan regions, and model adoption by the Zambian Ministry of Health.
My strengths range from data-driven research and quantitative analysis to optimization modeling and algorithmic programming. Here are some of my most-used coding skills.
A summary display of the attempt to improve bayesian networks by incorporating k-nearest neighbors and decision trees as base classifiers. Resulted in 28% increase accuracy in detecting credit card fraud.machine learning, bayesian nets, k-nearest neighbors, decision trees, big data, meta-learning
Used to help local businesses and governments improve NYC healthcare systems.
The prototype on the left shows heat maps indicating actionable areas where more doctors and health facilities would be needed to meet patients’ need for certain diseases.
Slides are available upon request.
An archive of both personal and school projects, ranging from Machine Learning and Computer Systems to Visualizations and Exploratory Data Analysis.data science
Almost double-majoring with fine arts for my undergrad, I have definitely thought of getting some certification in painting one day!
It's the possibility of having a dream come true that makes life interesting.Paulo Coelho
If I had asked people what they wanted, they would've said faster horses.Henry Ford
We make a living by what we get. We make a life by what we give.Winston Churchill
Got any questions? Contact me below!
Don't worry, I love coffee chats too.