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Data Scientist

Reads like an AI Engineer role: building products on existing AI models.

Pay
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Work setting
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Employment
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What you’ll work on

Full posting
  • Partner with stakeholders to find high-value opportunities and measure business outcomes

  • Design, build and deploy production-grade AI solutions across the Investment Bank

  • Create reusable products using LLMs, agentic systems, machine learning and rules-based analytics

  • Drive delivery from discovery and prototyping through integration, deployment and adoption

  • Develop reusable patterns for APIs, system integration, orchestration and observability

From the employer’s posting
partner with stakeholders to identify high-value opportunities and deliver measurable business outcomes
design, build and deploy production-grade AI solutions across the Investment Bank
create reusable products using LLMs, agentic systems, machine learning and rules-based analytics
drive delivery from discovery and prototyping through integration, deployment and adoption
develop reusable patterns for APIs, system integration, orchestration and observability
Apply at krb-sjobs:25008:5012

Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 12, 20261 day ago
Recorded sightings
3
Last seen by us
Nov 14, 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

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 4 and day 77.

From 51 similar postings that came down. Coming down is not always a hire.

krb-sjobs:25008:5012 is hiring

18 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

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Has krb-sjobs:25008:5012 posted this job before?

Yes. We’ve followed one other Data Scientist job there since November 2026. It is still up.

  1. Place not statedStill up after 1 day, first seen Nov 12
  2. This jobUp 1 day so far, first seen Nov 12

Demand for AI Engineer roles

New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.

Weekly new AI Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 7, the most 65, and the latest week had 65.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under AI Engineer, by the work the posting describes.

AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.

Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.

An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.

Job description

View original posting ↗

Are you passionate about using AI to transform the Investment Bank? Do you want to turn strategic opportunities into secure, scalable solutions with measurable business impact?

We’re looking for a Data Scientist to:

• partner with stakeholders to identify high-value opportunities and deliver measurable business outcomes such as revenue enablement, risk reduction and productivity
• design, build and deploy production-grade AI solutions across the Investment Bank
• create reusable products using LLMs, agentic systems, machine learning and rules-based analytics
• drive delivery from discovery and prototyping through integration, deployment and adoption
• develop reusable patterns for APIs, system integration, orchestration and observability
• ensure solutions are secure, reliable and maintainable through effective controls, monitoring, testing and documentation
• apply experimentation, quantitative analysis and model evaluation to guide design decisions and demonstrate impact
Source details

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