Lead Data Scientist

An exciting opportunity for a senior data scientist to be part of one of the world's largest banks. Based in Singapore, this role will be responsible for building data capabilities to drive analytics driven decision making processes across multiple product portfolios. Besides being strong in predictive modelling, the role requires excellent business stakeholder management skills.

If this role resonates with you, feel free to reach out for a confidential chat.

Responsibilities :

Engage with business stakeholders across countries and gather requirements and liaise with ETL team to get the required data preparation.

Engage and execute the dashboards on Tableau or similar visualization tools.

Explore statistical and automation tools like R, SAS, Python for predictive and prescriptive analytics.

Engage relevant technology teams to embed advanced statistical tools.

Provide insights to senior management and the network based on MIS and analytics.

Highlight any perceived risk and early alerts to the management based on data analytics.

Perform data validation and dashboard performance optimization.

Requirements :

A proven track record with 8+ years of relevant analytics work experience and demonstrated career progression / increase in responsibilities.

Experience of working on forecasting models in a banking or risk industries.

Exposure to statistical models, ML based forecasting models.

Strong Knowledge of data preparation tools like Alteryx, Dataiqu, SAS, R, Python tools.

Strong academic record : Degree in Finance, Statistics, Computer Science or related field.

Understanding of database structures.

Understanding in emerging cloud and smart technologies such as Azure, AWS, Cognitive Automation will be an added plus.

Proficient in SQL.

Strong understanding of Hadoop Database.

Understanding in emerging cloud and smart technologies such as Azure, AWS, Cognitive Automation will be an added plus.

Experience in data commercialization – facilitating partnerships and driving buy-in / adoption from stakeholders of varying levels.

Understanding of the ETL process.

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