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AVP, Specialist, Data Scientist, Institutional Banking Group
Reads like a ML Engineer role: putting models into production.
One Island East
Live, first seen by us 28 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employee Status: Full time
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign, develop and deploy GenAI and agentic AI solutions for Corporate Banking
Lead end-to-end delivery of AI initiatives such as eKYC automation and sales-support agents
Build analytics models for risk screening and dynamic pricing
Integrate AI solutions into production systems with business, product and data engineering teams
Set up frameworks for model development, evaluation and deployment
From the employer’s posting
Design, develop, and deploy Generative AI (GenAI) and Agentic AI solutions to drive digital transformation within Corporate Banking (IBG)
Lead the end-to-end implementation of AI-driven initiatives, including eKYC automation, workflow optimization, and intelligent sales-support agents
Develop and optimize advanced analytics models for risk screening and dynamic pricing
Collaborate with cross-functional teams, including business stakeholders, product managers, and data engineers, to integrate AI solutions into production systems
establishing robust frameworks for model development, evaluation, and deployment
What you’ll bring
All qualificationsCore experience
- Degree in Computer Science, Data Science, Statistics, or a related quantitative discipline.
- 8+ years of experience in data science/ML/AI, with a proven track record of delivering enterprise-scale, production-grade initiatives.
- Hands-on expertise in GenAI, LLMs, prompt engineering, RAG, and agentic frameworks (e.g., LangChain, LangGraph, Dify).
- Experience with cloud/big data platforms (GCP/Vertex AI, AWS, Cloudera, BigQuery, Spark, Kedro).
Qualification wording
Degree in Computer Science, Data Science, Statistics, or a related quantitative discipline.
8+ years of experience in data science/ML/AI, with a proven track record of delivering enterprise-scale, production-grade initiatives.
Hands-on expertise in GenAI, LLMs, prompt engineering, RAG, and agentic frameworks (e.g., LangChain, LangGraph, Dify).
Experience with cloud/big data platforms (GCP/Vertex AI, AWS, Cloudera, BigQuery, Spark, Kedro).
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 7, 202628 days ago
- Recorded sightings
- 81
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Sep 17, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
DBS is hiring
28 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- BigQuery
- GCP
- Spark
- NumPy
- pandas
- PySpark
- PyTorch
- scikit-learn
Where the posting names them
- 8+ years of experience in data science/ML/AI, with a proven track record of delivering enterprise-scale, production-grade initiatives. - Expert proficiency in AI/ML model development using Python/PySpark and core libraries (Pandas, NumPy, PyTorch, scikit-learn). - Hands-on expertise in GenAI, LLMs, prompt engineering, RAG, and agentic frameworks (e.g., LangChain, LangGraph, Dify).
- Hands-on expertise in GenAI, LLMs, prompt engineering, RAG, and agentic frameworks (e.g., LangChain, LangGraph, Dify). - Experience with cloud/big data platforms (GCP/Vertex AI, AWS, Cloudera, BigQuery, Spark, Kedro). - Advanced data visualization skills; Qlik Sense proficiency is mandatory.
Your next step
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Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Business Function
As the leading bank in Asia, Transformation & Data (T&D) supports our management in the implementation of the Group's agenda. The Data Chapter, organized under T&D, is committed to creating synergies between data analytics functions across the bank, establishing centres of excellence, shared services, and reusable data assets, as well as enhancing career opportunities and the sense of community for data professionals.
Responsibilities
- Design, develop, and deploy Generative AI (GenAI) and Agentic AI solutions to drive digital transformation within Corporate Banking (IBG).
- Lead the end-to-end implementation of AI-driven initiatives, including eKYC automation, workflow optimization, and intelligent sales-support agents.
- Develop and optimize advanced analytics models for risk screening and dynamic pricing to support strategic business decisions.
- Collaborate with cross-functional teams, including business stakeholders, product managers, and data engineers, to integrate AI solutions into production systems.
- Strengthen the bank's AI delivery capabilities by establishing robust frameworks for model development, evaluation, and deployment.
- Contribute actively to the bank's broader AI transformation agenda by identifying and piloting emerging AI technologies and methodologies.
Requirements
- Degree in Computer Science, Data Science, Statistics, or a related quantitative discipline.
- 8+ years of experience in data science/ML/AI, with a proven track record of delivering enterprise-scale, production-grade initiatives.
- Expert proficiency in AI/ML model development using Python/PySpark and core libraries (Pandas, NumPy, PyTorch, scikit-learn).
- Hands-on expertise in GenAI, LLMs, prompt engineering, RAG, and agentic frameworks (e.g., LangChain, LangGraph, Dify).
- Experience with cloud/big data platforms (GCP/Vertex AI, AWS, Cloudera, BigQuery, Spark, Kedro).
- Advanced data visualization skills; Qlik Sense proficiency is mandatory.
- Exceptional analytical, communication, and strategic acumen, with the ability to influence senior stakeholders and bridge business and technology teams.
Apply Now
We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.
Location:
One Island EastJob:
AnalyticsSchedule:
RegularEmployee Status:
Full timeSource details
Source notes
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- Pay
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- Location & working pattern
One Island East
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