Senior Data Scientist, Zalopay

The ideal candidate is an experienced solution and team builder who enjoys optimizing complicated problems or building them from the ground up. The data&AI team will work closely with our risk pillar owners, data engineers, and software engineers on new mechanism/solution initiatives and will ensure optimal data/model/system architecture is consistent throughout ongoing projects. The candidate must be self-directed and comfortable supporting the needs of multiple teams, systems, and products.

Responsibilities

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

• 6 - 10 years of relevant work experience with a large scale of REAL data;
• MSc/PhD in Computer Science, Mathematics, Data Science;
• Strong machine learning/statistics background with hands-on experience in industry, sourcing, cleaning, manipulating, and analyzing large volumes of data;
• Experience with end-to-end modeling projects emerging from research efforts;
• Willingness to understand a complex system and its various components;
• Great scripting and programming skills (fluent in Python, Java, GoLang);
• Experience with open-source machine learning libraries such as sci-kit-learn, weka, distributed/parallel big data processing architecture (e.g., Hadoop, Spark, MLlib), and deep learning framework (e.g., TensorFlow, Pytorch);
• Excellent problem-solving and communication skills;
• Ability to work well in a fast-paced culture and ability to manage multiple projects and deadline.