Peiyu Wang

Peiyu Wang's work experience begins with their role as a Master Thesis Student at Lannebo Fonder from December 2016 to June 2017. During this time, they worked on a thesis titled "Liquidity adjusted Value-at-Risk and its applications" and collaborated with the company to study how to adjust Value at Risk by incorporating exogenous and endogenous liquidity risk. They improved an algorithm for LVaR using Time Series analysis and Monte-Carlo simulation.

After completing their thesis, Peiyu Wang joined Klarna in September 2017 as an Analyst in the Credit Decision Optimization team. In this role, they maintained and improved models in Germany, Austria, and the Netherlands. They also created a new risk variable that contributed to reducing a specific payment method default rate from 8% to 2.4%. They utilized skills in R, Hive, Git, and Jira for their responsibilities until September 2018.

From September 2018 to March 2021, Peiyu Wang served as a Data Scientist in the Credit Modeling team at Klarna. They created and deployed models for predicting the probability of default, which were used for real-time credit decisioning. They implemented a logistic regression model in R for Norway and an Xgboost model in Python for Germany. They also played a significant role in managing over a million transactions weekly through the Python Xgboost model.

In March 2021, Peiyu Wang was promoted to the role of Senior Data Scientist/Competence Lead at Klarna. In this position, they were responsible for creating an AWS Pipeline for the full model lifecycle to scale up models for each sprint. This pipeline facilitated the expansion of the team's models to new countries and the continuous updating of existing country models. They also conducted experiments on models like Xgboost, Catboost, LightBGM, and k-NN. They utilized various technologies such as Amazon Sagemaker, Step Functions, Lambda, ECR, S3, and Python for these tasks.

Currently, Peiyu Wang is working as the Lead Data Scientist at Sprinque since February 2023. No further details regarding this role are provided.

Peiyu Wang obtained a Bachelor's degree in Mathematics from Sichuan University, where they studied from 2011 to 2015. Following this, they pursued a Master's degree in Financial Mathematics at Uppsala University from 2015 to 2017.

Apart from their formal education, Peiyu Wang has also obtained various certifications. Peiyu completed the "Analyze Datasets and Train ML Models using AutoML" course at Coursera in August 2021. In July 2020, they completed the "Agile with Atlassian Jira" course. Additionally, they have completed several Coursera courses, including the "Python 3 Programming Specialization" in June 2020, "Data Visualization with Python" in May 2020, "Applied Machine Learning in Python" in March 2020, "Data Analysis with Python" in July 2019, "Introduction to Data Science in Python" in June 2019, and "Learn to Program: The Fundamentals" in April 2019. Peiyu has also completed the "Advanced R Programming" course at Coursera in August 2018 and the "The R Programming Environment" course in August 2018. Prior to that, they completed the "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization" course in July 2018 and the "Neural Networks and Deep Learning" course in June 2018. In April 2018, they completed the "Big Data Analysis with Scala and Spark" course at Coursera. Peiyu has also completed the "R Programming Track" and the "Data Manipulation in R with dplyr Course" at DataCamp in November 2017 and October 2017, respectively.

It is worth noting that Peiyu Wang has another certification, "DataRobot Essentials for Klarna," from DataRobot. However, the month and year of obtaining this certification are not provided.