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Day 3
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.
Data Scientist, Investment Bank
Reads like an AI Engineer role: building products on existing AI models.
Location not stated
Actively hiring, first seen by us 3 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingPartner with stakeholders to find high-value opportunities and measure business outcomes
Build and deploy AI solutions across the Investment Bank
Develop reusable products and components using LLMs, agentic systems, ML and rules-based analytics
Integrate solutions with APIs, enterprise systems and data platforms
Test, monitor and document solutions so they are secure, reliable and maintainable
From the employer’s posting
Partner with stakeholders to identify high-value opportunities and contribute to business outcomes
Build and deploy AI solutions across the Investment Bank
Develop reusable products and components using LLMs, agentic systems, machine learning, and rules-based analytics
Integrate solutions with APIs, enterprise systems, and data platforms
Ensure solutions are secure, reliable, and maintainable through appropriate testing, monitoring, controls, and documentation
Posting record
Report an errorActively hiringFirst seen by us 3 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 10, 20263 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 13, 2026
- Employer says posted
- Oct 9, 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
krb-sjobs:25008:5012 is hiring
18 open jobs
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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.
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
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 contribute to business outcomes such as revenue enablement, risk reduction, and productivity improvement
• Build and deploy AI solutions across the Investment Bank
• Develop reusable products and components using LLMs, agentic systems, machine learning, and rules-based analytics
• Contribute throughout the delivery lifecycle, from discovery and prototyping through integration, deployment, and adoption
• Integrate solutions with APIs, enterprise systems, and data platforms
• Ensure solutions are secure, reliable, and maintainable through appropriate testing, monitoring, controls, and documentation
• Apply experimentation, quantitative analysis, and model evaluation to inform design decisions and demonstrate impact
We’re looking for a Data Scientist to:
• Partner with stakeholders to identify high-value opportunities and contribute to business outcomes such as revenue enablement, risk reduction, and productivity improvement
• Build and deploy AI solutions across the Investment Bank
• Develop reusable products and components using LLMs, agentic systems, machine learning, and rules-based analytics
• Contribute throughout the delivery lifecycle, from discovery and prototyping through integration, deployment, and adoption
• Integrate solutions with APIs, enterprise systems, and data platforms
• Ensure solutions are secure, reliable, and maintainable through appropriate testing, monitoring, controls, and documentation
• Apply experimentation, quantitative analysis, and model evaluation to inform design decisions and demonstrate impact
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Location not supplied.
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.