Assistant Professor in Actuarial Data Science (T&R)

Heriot-Watt University
Kilmarnock
19 hours ago
Create job alert
Assistant Professor in Actuarial Data Science (T&R)

Directorate: School of Mathematical and Computer Sciences


Salary: Grade 7 – £37,694 – £47,389 / Grade 8 – £47,389 – £58,225


Contract type: Full Time (1FTE), Open Ended


Rewards and Benefits: 33 days annual leave, plus 9 buildings closed days for all full time staff (Part time workers pro rata by FTE). Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm.


Seniority level: Mid‑Senior level


Job function: Education and Training


Industries: Higher Education


Detailed Description

The Department of Actuarial Mathematics and Statistics at Heriot‑Watt University, Edinburgh, seeks to enhance its research and teaching in actuarial science and statistics by appointing an Assistant Professor in Actuarial Data Science, or a related actuarial statistics area. Applicants from statistical learning, actuarial statistics or related areas are encouraged. Candidates interested in the university’s multi‑disciplinary Global Research Institutes in climate change & sustainability or healthcare are especially welcome.


Key Duties and Responsibilities

  • Lead, carry out and publish internationally excellent research in actuarial data science, actuarial statistics or a related field.
  • Apply for research funding via grant proposals or industry funding to build a research group.
  • Undertake knowledge exchange activities to promote and disseminate research.
  • Perform administrative and recruitment activities as required.
  • Develop and deliver innovative teaching at undergraduate and postgraduate level.
  • Report to the Head of Department, maintaining and enhancing the School’s reputation for excellence.

Education, Qualifications and Experience

Essential criteria:



  • E1. PhD in actuarial science, statistics, or a related field.
  • E2. Track record of high-quality research in actuarial data science with internationally excellent publications.
  • E3. Demonstrable teaching experience and skills to supervise undergraduate and postgraduate dissertations.
  • E4. Excellent interpersonal and teamwork skills.
  • E5. Potential, ambition and plans to obtain research funding.
  • E6. Ability to supervise PhD students successfully.

Desirable criteria:



  • D1. Track record of obtaining research funding.
  • D2. Successful supervision of PhD students and/or post‑doctoral researchers.
  • D3. Potential to lead research strategy and develop learning and teaching activities.

How to Apply

Submit via the Heriot‑Watt University online recruitment system:



  1. Cover letter describing interest and suitability.
  2. Full CV, including publication list.
  3. Outline of research plans for next few years.
  4. One-page summary of teaching philosophy or approach.

Applications accepted until midnight on Sunday 18th January 2026.


Contact

For questions, contact Head of Department, Professor George Streftaris – .


Equality, Diversity and Inclusion

Heriot‑Watt University is committed to securing equality of opportunity in employment and creates an environment of merit-based selection, training, promotion and treatment. Diversity and inclusion are central to our culture. For more information, see https://www.hw.ac.uk/uk/services/equality-diversity.htmand also our Disability Inclusive Science Careers at https://disc.hw.ac.uk/.


#J-18808-Ljbffr

Related Jobs

View all jobs

Assistant Professor in Actuarial Data Science (T&R)

Assistant Professor in Statistical Data Science

Assistant Professor in Statistical Data Science

Actuarial Data Science: Assistant Professor

Assistant Professor in Statistical Data Science

Assistant Professor of Mathematics — Data Science & Global Teaching

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.