Lead Data Scientist, ZaloPay

Design and analyze experiments to pilot, test and apply new features & solutions;
Foster a culture of ownership, accountability, testing, and measurement; as well as continuous improvement through mentoring, feedback, and metrics.
Conduct end-to-end data processing, troubleshooting and problem diagnosis in the whole life cycle of AI/ML development and operation;
Own, design, develop and test large-scale data science pipeline and algorithms that are built for speed, scale and usability;
Evaluate and recommend tools, technologies and processes to ensure the highest quality solutions;
Collaborate with other engineers and team members to evaluate and improve the core components of autonomous systems;
Extract, analyze and apply data-mining/AI/ML techniques to large structured and unstructured datasets;
Analyze and improve existing data sources, models, strategies and metrics;
Research and investigate academic and industrial AI/ML techniques for product improvements;
Focus on bringing statistical depth, analytical insights, and accurate interpretation of data;
Report, visualize and communicate results & impacts;
Stay current on published state-of-the-art algorithms and competing technologies;
Identify any product/functionality/technical gaps required to deliver a solution and collaborate with internal teams to define the necessary enhancements to support delivery;

Ability to work well in a fast-paced culture and ability to manage multiple projects and deadlines.
MSc/PhD in machine learning, statistics, math, data science, computer science or other closely related areas;
Demonstrated leadership capability in leading and motivating a team of 5+ people;
5+ years relevant work experience with large amounts of REAL data;
Strong machine learning/statistics background with hands-on experience in academia and/or industry, sourcing, cleaning, manipulating and analyzing large volumes of data;
Experience with open-source machine learning libraries such as scikit-learn, weka, distributed/parallel big data processing architecture (e.g., Hadoop, Spark, MLlib) and deep learning framework (e.g., TensorFlow, Pytorch);
Willingness to understand a complex system and its various components;
Experience with end-to-end modeling projects emerging from research efforts;
Excellent problem-solving and communication skills;
Great scripting and programming skills (fluent in Python, Java, Scala);

Cập nhật gần nhất lúc: 2021-07-20 11:51:07