About the job
Our team plays a crucial role in ensuring the company’s success. We seek people who are willing to learn and put in the effort to solve problems. Our challenges are not your regular day-to-day problems - you’ll be part of a team that’s developing new solutions to new challenges. It’s working fast, at scale, and we’re making a difference. We are looking for talents to join us on this exciting journey!
Responsibilities
Build rules, algorithms, and machine learning (ML) models to identify and mitigate business risks on the e-commerce platform by extracting valuable business insights/information from raw data and data sources.
Analyze large amounts of information to discover trends and patterns in data through probability and statistical analysis and automate the collection processes.
Optimize machine learning modeling infrastructure to detect fraudulent activities and anomalies on the e-commerce platform.
Present information using data visualization techniques.
Develop classification and regression algorithms using machine learning techniques.
Propose solutions and strategies to improve privacy and security functions.
Collaborate with cross-functional teams to optimize overall project goals.
Qualifications
Minimum
Must have a Master’s degree or foreign equivalent degree in Computer Science, Engineering (any), Information Technology, Data Science, Statistics, Mathematics, or a related quantitative field, and 1 year of related work experience; OR a Bachelor’s degree or foreign equivalent degree in Computer Science, Engineering (any), Information Technology, Data Science, Statistics, Mathematics, or a related quantitative field, and 3 years of related work experience.
Of the required experience, must have 1 year of experience in each of the following:
Using SQL queries and data visualization tools to gather, process, visualize, and analyze large quantities of data to detect trends and anomalies in support of business opportunity identification;
Analyzing large quantities of data to detect anomalies using Python and statistical analysis techniques;
Building, tuning, and validating statistical models for regression and classification problems in Python or R;
Developing and deploying large-scale machine learning systems; and
Providing data-driven insights and recommendations to mitigate insufficiencies models based on model performance, regulations, and business requirements.
Preferred
No preferred qualifications listed.