Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Assistant Professor (Education) in Data Science

The London School of Economics and Political Science (LSE)
City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Analyst – Senior Consultant, Assistant Manager, Manager - Advisory Consulting

Funds Technology – Data Analyst Manager/ Assistant Manager/ Senior Consultant

Funds Technology - Data Analyst Manager/ Assistant Manager/ Senior Consultant

Data Analyst Senior Consultant, Assistant Manager, Manager - Advisory Consulting

Funds Technology Data Analyst Manager/ Assistant Manager/ Senior Consultant

Senior Data Scientist, Payments Intelligence

Assistant Professor (Education) in Data Science

LSE is committed to building a diverse, equitable and truly inclusive university. As an equal opportunities employer, we encourage applications from women and ethnic minorities under‑represented at this level. All appointments will be made on merit or skill and experience relative to the role.

Department of Statistics

Salary: no less than £68,087 per annum. Salary scale can be found on the LSE website.

Position overview: This Education Career Track post is suitable for outstanding teachers in data science with a focus on computational aspects. The postholder will join a vibrant research and teaching environment in the Department of Statistics, supporting the MSc Data Science, the new BSc Economics and Data Science, and other departmental courses. Tenable from 1 September 2026.

  • Teaching responsibilities: Deliver undergraduate and postgraduate courses in programming, databases, distributed computation and other computer-science subjects; use modern data‑science software; incorporate real‑world datasets.
  • Other responsibilities: Manage course delivery, contribute to curriculum development, support students and collaborate across departments.
  • Qualifications: Proven track record of excellence in teaching and a strong commitment to education.
  • Strong record in teaching computer‑science courses: programming, databases, distributed computation, large‑scale machine‑learning tasks.
  • Experience with modern data‑science tools and technologies.
  • Interest or experience using real‑world datasets.
  • Strong interpersonal and networking skills.

Benefits: Competitive salary, occupational pension scheme, collegial environment, excellent support, training and development opportunities.

How to apply: Please go to https://www.jobs.lse.ac.uk and submit your application. For technical questions, use the ‘contact us’ links on the LSE Jobs page. For role‑specific questions, email .

Closing date for receipt of applications: 14 December 2025 23:59 UK time. Late applications will not be accepted.


#J-18808-Ljbffr

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.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.