ZaloPay, Data Scientist (22-PDP-1158)

We're a Fintech product in Viet Nam with young people and full of energy. Our aim is to optimize product across the entire user journey, identify and create new audiences. We are looking for a Data Scientist to join our Data Science Team. You’ll be part of a team that is disrupting the industry with innovative attribution models and building the future analytics platform to be used by many teams (Tech, Promotion, etc.) for User Behavior, Campaign performance and market insights. You’ll be working on very exciting projects using big data technologies with terabytes of data coming from different source.

Responsibilities:

• Work with many teams (PO, Tech, BO) to understand dataflow, cashflow
• Identify problems and propose recommendations
• Focus on bringing statistical depth, analytical insights, and accurate interpretation of data
• Measure system performance and also deeper understand trends by providing insights and recommendations based on large amounts of data from various sources
• Design innovative attribution models to implement valuable metrics and better address system enhancement, user behavior
• Build and maintain visually appealing and engaging dashboards for stakeholders
• Work with Data Engineers to help define the data standards and requirements helping to ensure our systems are running correctly and efficiently.
• Involve in the development and evolvement of the data architecture
• Support internal training and proper documentation ensuring the successful onboarding of new team members

Requirements

Requirements:

• 2+ years relevant work experience with large amounts of data
• Education background in machine learning, statistics, math, data science, computer science or other closely related area
• 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 numpy, pandas, scikit-learn, distributed/parallel big data processing architecture (e.g., Hadoop, Spark, MLlib) and deep learning framework (e.g., TensorFlow, Pytorch)
• Quickly understand the business domain (FinTech, AdTech knowledge is a plus)
• Can plan, prioritize and troubleshoot
• Experience with recommendation systems is a plus
• Experience with data science models in finance domain or CRM (e.g., credit scoring, CLV, churn, etc.) is a plus.