About

Lawin Steve Mathew Lasington is a highly skilled Data Scientist with over 5 years of experience in the field. He is currently working as a Data Scientist in Machine Learning at Grubhub, where he applies his expertise in ML to improve the company's operations. Lawin's educational background includes a Master's degree in Quantitative Finance from Rutgers Business School, which has equipped him with a strong foundation in statistical analysis and financial modeling. In his previous role as a Data Scientist at Intercontinental Exchange, Lawin used regression models, time series models, and Bayesian statistics in Python to better understand the financial market. He also applied machine learning techniques such as classification, clustering, optimization, deep neural networks using Python libraries including Scikit-learn, XGBoost, Keras, and Tensorflow to create models. Lawin worked with large amounts of data using Python and SQL to create data pipelines, and performed data wrangling using Pandas, NumPy, and SQL on a daily basis. He also worked with cross-functional teams to make model enhancements and communicate results to a wide audience. As a Data Scientist Intern at Quantz Capital Management, Lawin processed and cleaned time series of various factor returns. He performed K-means clustering to identify factor buckets, which in turn were used in portfolio construction and portfolio optimization. Lawin also worked on combining traditional signals and certain factor buckets with alternative signals to demonstrate the advantages of combining traditional and alternative data. Lawin's technical skills include expertise in ML, Data Science, Research Science, SQL, Python, XGBoost, Keras, Scikit, Tensorflow, Pandas, and Neural Networks. He is a highly motivated individual who is passionate about using data to solve complex problems.