Zalopay, Senior Data Scientist

**Risk Management team** at ZaloPay gather highly motivated team players who dedicate in building ZaloPay as the most trusted financial service and best against to bad actors in Vietnam fintech market. By developing and adopting advanced tech-driven prevention mechanisms/solutions while focusing on the user growth and customer experience, we aim to make risk management capability as a core and key differentiation of ZaloPay comparing to other competitors. This helps our business grow sustainably and provide affordable services to all Vietnamese people.

**How will you make an impact?**
- We are looking for a savvy, motivated, team-oriented
- **Data Scientist** to join our
- _Risk Data Science team_. The team is responsible for bringing insights from data to assess and manage multiple financial risk exposures (e.g., promotion abuse, ATO, KYC fraud, payment fraud), as well as developing and maintaining controls, strategies, solutions, and experiences related to the end-to-end management of these exposures.- The hire will be responsible for
- **the full life-cycle of data product (i.e., from problem identification, to data product design & development, deployment, monitoring & optimization in production**
**)**
***:

- of _
- our_
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- Risk Data Solutions & Analytics_. Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies; and communicating with stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets.**What will you do?**- Focus on bringing statistical depth, analytical insights, and accurate interpretation of data;
- Own, design, develop and test large-scale data science pipeline 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;
- 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.

**Yêu cầu**:

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- **How you will get here?**- 2+ years relevant work experience with large amounts of REAL data;
- MSc/PhD in machine learning, statistics, math, data science, computer science or other closely related areas;
- 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 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, Scala);
- 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);
- Excellent problem-solving and communication skills;
- Ability to work well in a fast-paced culture and ability to manage multiple projects and deadlines.