Data Science Lead

DBS Bank Limited; Singapore; On-site; SGD 150,000 - 200,000; Full time

Job summary

A leading financial institution seeks a Lead Data Scientist for its Institutional Banking Group Data Chapter. This pivotal role involves managing a data science team to deliver impactful AI solutions, requiring a PhD and significant industry experience. You will drive decision-making through advanced data capabilities while overseeing design and development aligned with bank priorities.

Qualifications

• Minimum 10 years of applied data science experience.
• Strong technical expertise in AI/ML, data mining.
• Experience with large datasets and deploying data solutions.

Responsibilities

• Manage a team of data scientists to leverage AI & Generative AI.
• Oversee design and delivery of AI/ML strategies.
• Engage with stakeholders to drive data science value.

Skills

Deep learning

Classification

Optimization

Recommender systems

Anomaly detection

Time-series forecasting

Education

PhD or equivalent in Computer Science, Statistics, Mathematics, Operations Research

Job description

Business Function

The Institutional Banking Group Data Chapter is committed to building a data driven organization and maximizing the key data capabilities to transform how IBG does business. Data impacts IBG's businesses every day, and a culture of relentlessly using data and business intelligence will enable IBG to achieve exponential growth.

Key Responsibilities

As the Lead Data Scientist, you will manage a team of data scientists within IBG Data Chapter to deliver business impact by leveraging AI & Generative AI. You will lead complex data science projects that drive decision-making in IBG, in areas across revenue generation, risk management, and productivity etc.

• Oversee the team in the design, development and delivery of AI/ML and Generative AI strategies and capabilities to support IBG's strategic priorities, in alignment with the bank's AI industrialization agenda.
• Engage with senior management and business stakeholders to identify opportunities where data science can deliver value.
• Provide leadership to the team in collaborating with various stakeholders from business and technology throughout the analytics lifecycle, from requirements gathering, solution iteration, deployment, to ongoing enhancements.
• Ensure robust model governance, including performance monitoring, validation, and re-calibration, in line with governance standards and best practices.
• Drive productivity and impact within the team by optimizing ways of working, by e.g. prioritization, building of reusable assets, leveraging Generative AI tools, and facilitating time-to-value.
• Stay abreast of industry trends, emerging technologies, and best practices in data science and facilitate knowledge sharing for capability building.

Key Requirements

• PhD or equivalent advanced qualifications in Computer Science, Statistics, Mathematics, Operations Research, or in fields related to AI/ML, data mining, deep learning, etc.
• Deep technical expertise in areas such as recommender systems, classification, optimization, deep learning, graph mining, anomaly detection, time-series forecasting, causal and statistical reasoning.
• Minimum 10 years of applied data science experience in industry (ideally banking, e-commerce, technology & telecommunications or equivalent) with proven track record of delivering business impact. Academic experience with track record of innovative research will be a plus.
• Rich experience working on large structured & unstructured datasets, and implementing large-scale data science solutions. Proven track record of deploying solutions into production, integrating them into workflows, and implementing continuous monitoring and enhancements. Experience in implementing large language models at scale will be a plus.
• Strong communication, interpersonal and stakeholder management skills, with an ability to present analysis and insights in a manner accessible by non-practitioners.
• Resourceful attitude with a 'can-do' spirit.

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