Data Specialist, Payments Team

We focus on building a strong culture of data-driven decision-making, and humanising big data sits at the heart of our strategic planning. As we continue to develop impactful solutions to power the success of our business, data-driven insights are our biggest ally in navigating the fast-changing technological landscape. 

As an Advanced Data Specialist in the Fraud Team, you will oversee the day-to-day fraud management and develop new techniques to detect and prevent the potential abuse of our platform. This includes defining performance metrics, analysing trends, identifying new fraud behaviour and modus operandi, scaling operational workflows, and designing new tools or processes to detect and prevent dishonest practices on our platform.

We are looking for hands-on, motivated self-starters who are driven to leverage the power of using data to drive informed business decisions.

Job description

• Build data visualisation and dashboard for the business
• Deliver accurate regular and ad-hoc performance tracking and analysis to drive traffic, transactions and processes
• Ad-hoc analysis based on strategic direction of the business and deep dive into specific area / trend
• Make recommendations based on historical data and predict trends
• Design, develop and implement statistical models, as well as interpret and present statistical outcomes to support the organisation’s operations and execution of key business strategies
• Design and conceptualize solution that address the organisation’s challenges through use of big data analytics and process large amount of data by applying algorithms
• Collaborate with stakeholders to build data analytics capabilities, conduct feasibility studies.
• Devise methods and strategies to obtain and extract data to derive business insights

Requirement

• Degree holder preferably in a technical field such as Computer Science, Engineering, Statistics, etc; or Degree holder in a business related field as long as there is a strong interest in data analysis;
• Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources
• Experience and knowledge of analytical and statistical modelling techniques: hypothesis development, designing tests/experiments, analysing data, regression (multiple, logistic, log-linear), neural network, decision tree, variable selection, etc
• Experience working with data visualization to inform decisions
• Excellent working knowledge of data analysis with Python, R, SQL or other advanced programming languages;
• Good communications skills in English;

JOIN US!