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 a Data Specialist in the Payments & Fraud Team, you will oversee the day-to-day payments management and develop new features to improve our payment pipeline.  This includes defining performance metrics, analysing trends, scaling operational workflows, strategising and collaborating with tech teams on data collection to enable business decisions for opspay optimisation. Also design, develop and implement machine learning / causal inference models and present the explainable outcomes to support Shopee Latam operations and execution of key business strategies.

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
  • Promote data-driven decision by aggregating and surfacing data across multiple platforms
  • Ad-hoc analysis based on strategic direction of the business and deep dive into specific area
  • 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
  • Develop metrics that cut beyond surface-level and partner with engineering to ensure appropriate data capture
  • Collaborate with stakeholders to build data analytics capabilities, conduct feasibility studies.
  • Perform complex analysis on simulations on payments pipeline usage behavior

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;
  • Excellent working knowledge with query language (SQL, NoSql, MSSQL, …)
  • Experience working knowledge with data visualization (DataStudio, PowerBI, Tableau…)
  • Experience working knowledge with data processing languages such as (Python, Go, Spark…)
  • Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources
  • 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
  • Basic knowledge of the Hadoop ecosystem.
  • Good communications skills in English

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