Data Visualization Manager

1 dia atrás

Sao Paulo, Brasil Shopee Tempo inteiro

The Fraud team oversees the day-to-day fraud management and develops new techniques to detect and prevent the potential abuse of our platform. This includes defining performance metrics, analyzing trends, identifying new fraud behaviors and modus operandi, scaling operational workflows, and designing new tools or processes to detect and prevent dishonest practices on our platform. When some fraud suspicious is detected by payments, or some partner alerts us about fraud events, Payments drive the event to the Fraud team.

We focus on building a strong culture of data-driven decision-making, and humanizing 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 Visualization Manager, you will oversee the day-to-day business operations. This includes defining performance metrics, analyzing trends, scaling operational workflows, strategizing, and collaborating with tech teams on data collection to enable business decisions and strategies. Also design, develop and implement machine learning / causal inference models and present the explainable outcomes to support Shopee Latam Operations.

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
- Devise methods and strategies to obtain and extract data to derive business insights
- Build strategics DataMarts
- Monitoring fraud operations

**Requirement**
- Availability to work in São Paulo - a hybrid working model
- 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;
- Data Visualization skills
- Storytelling with data experience
- 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

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