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Assistant Vice President, Specialist Data Scientist, Transformation and Data

Mumbai

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
Apply at DBS

What you’ll work on

Full posting
  • Collaborate with business units across DBS to identify opportunities where data science and machine learning can drive business value and optimize banking processes.

  • Design, build, and deploy robust machine learning models, focusing on end-to-end model development from data ingestion to production.

  • Lead the development and execution of Generative AI (GenAI) Proof of Concept (POC) initiatives, evaluating their feasibility, performance, and alignment with business goals.

From the employer’s posting
Responsibilities Collaborate with business units across DBS to identify opportunities where data science and machine learning can drive business value and optimize banking processes. Design, build, and deploy robust machine learning models, focusing on end-to-end model development from data ingestion to production.
Collaborate with business units across DBS to identify opportunities where data science and machine learning can drive business value and optimize banking processes. Design, build, and deploy robust machine learning models, focusing on end-to-end model development from data ingestion to production. Lead the development and execution of Generative AI (GenAI) Proof of Concept (POC) initiatives, evaluating their feasibility, performance, and alignment with business goals.
Design, build, and deploy robust machine learning models, focusing on end-to-end model development from data ingestion to production. Lead the development and execution of Generative AI (GenAI) Proof of Concept (POC) initiatives, evaluating their feasibility, performance, and alignment with business goals. Perform complex data analysis, feature engineering, and statistical modeling to extract actionable insights from large-scale banking datasets.

What you’ll bring

All qualifications

Core experience

  • Degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Proven experience in data science and hands-on model development within a professional environment.
  • Prior experience or strong domain knowledge in the banking or financial services industry.
  • Demonstrated experience with Generative AI (GenAI) technologies, Large Language Models (LLMs), and conducting POC evaluations.
  • Proficiency in programming languages such as Python or R, and strong SQL skills for data extraction and manipulation.
  • Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and cloud platforms (e.g., AWS, GCP, or Azure).
Qualification wording
Degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
Proven experience in data science and hands-on model development within a professional environment.
Prior experience or strong domain knowledge in the banking or financial services industry.
Demonstrated experience with Generative AI (GenAI) technologies, Large Language Models (LLMs), and conducting POC evaluations.
Proficiency in programming languages such as Python or R, and strong SQL skills for data extraction and manipulation.
Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and cloud platforms (e.g., AWS, GCP, or Azure).

Tools in this posting

  • Python
  • R
  • SQL
  • AWS
  • Azure
  • GCP
  • PyTorch
  • scikit-learn
  • TensorFlow
Source — Tool mentions in context
- Demonstrated experience with Generative AI (GenAI) technologies, Large Language Models (LLMs), and conducting POC evaluations. - Proficiency in programming languages such as Python or R, and strong SQL skills for data extraction and manipulation. - Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and cloud platforms (e.g., AWS, GCP, or Azure).
- Proficiency in programming languages such as Python or R, and strong SQL skills for data extraction and manipulation. - Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and cloud platforms (e.g., AWS, GCP, or Azure). - Strong analytical and problem-solving skills, with the ability to present complex technical concepts to diverse stakeholders.

Posting record

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First seen by us
Oct 29, 2026 · today
Recorded sightings
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Job description

View original posting ↗

Business Function

Group Operations enables and empowers the bank with an efficient, nimble, and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation. In Group Operations, we manage the majority of the Bank's operational processes and inspire to delight our business partners through our multiple banking delivery channels. As an Operations Department, we embrace and reinforce the strong PRIDE! culture that is built up in DBS. This is done through strategic focus on training and improving staff capability, empowerment, productivity, teamwork, innovation & technology, managing operational risks & strongly collaborating with our business partners in delivering excellent RED service to our customers.

Responsibilities

  • Collaborate with business units across DBS to identify opportunities where data science and machine learning can drive business value and optimize banking processes.
  • Design, build, and deploy robust machine learning models, focusing on end-to-end model development from data ingestion to production.
  • Lead the development and execution of Generative AI (GenAI) Proof of Concept (POC) initiatives, evaluating their feasibility, performance, and alignment with business goals.
  • Perform complex data analysis, feature engineering, and statistical modeling to extract actionable insights from large-scale banking datasets.
  • Establish evaluation frameworks and metrics to monitor, validate, and continuously improve the performance of deployed models and GenAI solutions.
  • Partner with data engineers and IT teams to integrate data science models into scalable, secure production environments.

Requirements

  • Degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Proven experience in data science and hands-on model development within a professional environment.
  • Prior experience or strong domain knowledge in the banking or financial services industry.
  • Demonstrated experience with Generative AI (GenAI) technologies, Large Language Models (LLMs), and conducting POC evaluations.
  • Proficiency in programming languages such as Python or R, and strong SQL skills for data extraction and manipulation.
  • Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and cloud platforms (e.g., AWS, GCP, or Azure).
  • Strong analytical and problem-solving skills, with the ability to present complex technical concepts to diverse stakeholders.

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:

Mumbai

Job:

Analytics

Schedule:

Regular

Employee Status:

Full time
Source details

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