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Senior Data Scientist (Safety)

London · London, United Kingdom

Live, first seen by us 72 days ago
Pay
Pay not listed
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Data Science › National Security & Safety — team source
Department: Data Science › National Security & Safety
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Do you require visa sponsorship, either now or in the future, to work in the UK? This would cover either upon joining Faculty or if a visa needs to be extended at a later date.
From the employer’s application form

What you’ll work on

Full posting

As a Senior Data Scientist at Faculty, you will lead high-impact AI safety projects and shape the technical direction of upstream evaluation standards.

You will invent novel evaluation frameworks, design robust software architectures, mentor technical team members, and ensure delivery rigour across engagements—all while partnering with Frontier Labs to solidify our reputation as a leader in practical, high-stakes AI safety.

  • Lead project teams delivering AI safety solutions and evaluation standards to Frontier Labs

  • Design core experiment methods and software architecture for new engagements

  • Mentor technical team members on projects and their professional growth

  • Work with commercial teams to scope projects and assess technical feasibility

  • Ensure rigorous scientific method and technical best practices across project lifecycles

From the employer’s posting
As a Senior Data Scientist at Faculty, you will lead high-impact AI safety projects and shape the technical direction of upstream evaluation standards. This role requires hands-on scientific thinking and technical excellence combined with strong project leadership.
You will invent novel evaluation frameworks, design robust software architectures, mentor technical team members, and ensure delivery rigour across engagements—all while partnering with Frontier Labs to solidify our reputation as a leader in practical, high-stakes AI safety.
Leading project teams that deliver upstream AI safety solutions and evaluation standards to Frontier Labs
Conceiving core scientific experiment designs and building the associated software architecture for new engagements
Mentoring technical team members on projects and supporting their professional growth through scientific guidance
Partnering with commercial teams to shape project scope, assess technical feasibility
Ensuring rigorous scientific methodology and technical best practices are followed across the project lifecycle.

What you’ll bring

All qualifications

Core experience

  • Senior experience in data science, upstream safety research, or a quantitative academic field
  • Strong experiment design methodology
  • Strong Python programming with NumPy and Pandas
  • Commercial awareness to bridge science and client requirements
Qualification wording
You possess senior experience in a professional data science role, upstream safety research, or a quantitative academic field
with strong experiment design methodology
You demonstrate strong programming skills in Python using core scientific libraries (NumPy, Pandas)
You demonstrate commercial awareness, with the ability to bridge complex scientific work with client requirements in Frontier Labs.

Tools in this posting

  • Python
  • NumPy
  • pandas
Source — Tool mentions in context
- You possess senior experience in a professional data science role, upstream safety research, or a quantitative academic field with strong experiment design methodology. - You demonstrate strong programming skills in Python using core scientific libraries (NumPy, Pandas) and , ideally, evaluation frameworks and tooling (e.g. Inspect AI) and agentic harnesses. - You bring deep curiosity and expertise across the data science toolkit, with a drive to develop novel evaluation standards for specialized domains.

Posting record

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Status in our records
Live
First seen by us
Aug 27, 202672 days ago
Recorded sightings
135
Last seen by us
Nov 8, 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 72

Up longer than most. Similar jobs usually come down between day 7 and day 57.

From 10,558 similar postings that came down. Coming down is not always a hire.

Faculty is hiring

36 open jobs

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

  • Data Scientist hiring is picking up
  • Its jobs tend to stay up a long time
Hiring record

Your next step

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Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,815.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 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 Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Why Faculty?


We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.

We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.

Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.

AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.

About the team

 

Our National Security and AI Safety business unit is dedicated to advancing the responsible development and deployment of AI in support of national security and global stability. From strengthening mission-critical capabilities across national security and intelligence, to working with frontier labs to provide robust AI safety red teaming and evaluation, we work at the frontier of high-stakes, high-impact missions.

We understand that powerful AI systems bring both transformative opportunities and complex risks and we are proud to partner with Government and the biggest tech organisations in the world to ensure AI is not just transformative but is also secure, trustworthy and safe for all.

 
 

About the role

 

As a Senior Data Scientist at Faculty, you will lead high-impact AI safety projects and shape the technical direction of upstream evaluation standards. This role requires hands-on scientific thinking and technical excellence combined with strong project leadership.

You will invent novel evaluation frameworks, design robust software architectures, mentor technical team members, and ensure delivery rigour across engagements—all while partnering with Frontier Labs to solidify our reputation as a leader in practical, high-stakes AI safety.

What you'll be doing:

 
  • Leading project teams that deliver upstream AI safety solutions and evaluation standards to Frontier Labs.

  • Conceiving core scientific experiment designs and building the associated software architecture for new engagements.

  • Mentoring technical team members on projects and supporting their professional growth through scientific guidance.

  • Partnering with commercial teams to shape project scope, assess technical feasibility, and translate complex problems into rigorous frameworks.

  • Contributing to Faculty’s thought leadership by advancing the science of AI evaluations, public speaking, or publishing open-source research.

  • Ensuring rigorous scientific methodology and technical best practices are followed across the project lifecycle.

     

Who we're looking for:

 
  • You possess senior experience in a professional data science role, upstream safety research, or a quantitative academic field with strong experiment design methodology.

  • You demonstrate strong programming skills in Python using core scientific libraries (NumPy, Pandas) and , ideally, evaluation frameworks and tooling (e.g. Inspect AI) and agentic harnesses.

  • You bring deep curiosity and expertise across the data science toolkit, with a drive to develop novel evaluation standards for specialized domains.

  • You exhibit high technical rigor and a collaborative mindset focused on nurturing team capabilities and sharing technical knowledge.

  • You demonstrate commercial awareness, with the ability to bridge complex scientific work with client requirements in Frontier Labs.

  • You excel at scientific problem-solving, scoping technical work, and guiding project execution to meet high standards on structured timelines.

 

Our Interview Process

 
  1. Talent Team Screen (30 minutes)

  2. Take Home Technical Assessment

  3. Technical Interview (90 minutes)

  4. Commercial Interview (60 minutes)

     

Our Recruitment Ethos

We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.

If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.

A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.

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Pay

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Location & working pattern

London, United Kingdom

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