Principal Data Scientist

Discovered MENA
London
1 year ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist: Scale ML for Audiences (Hybrid)

Principal Data Scientist London, United Kingdom

Principal Data Scientist: ML Leader, Mentor, Hybrid Role

Principal Data Scientist - Lead & Scale Production ML

Principal Data Scientist

London (Hybrid)

Salary: £100,000 - £150,000 GBP + equity


We are hiring multiple data positions including a Principal Machine Learning Scientist with a sharp focus on optimisation. In this role, you’ll lead the charge in merging cloud infrastructure, DevOps, and machine learning to create and deploy advanced optimization models across diverse industries. Your expertise will drive our technological evolution, enhancing our product offerings and solving complex challenges at scale.


Discover the Responsibilities:

  • Develop Scalable Optimization Solutions:Design robust optimization solutions that significantly improve efficiency using the latest in machine learning and operations research.
  • Prototype to Production:Transition optimization model prototypes into fully integrated, scalable applications that deliver real business impact.
  • Drive Business Insights:Use optimization models to generate actionable insights, driving strategic decisions and communicating them effectively to stakeholders.
  • Optimization Specialization:Develop cutting-edge algorithms to solve complex problems in logistics, scheduling, resource allocation, and more.
  • Ensure Data Integrity:Conduct thorough data audits to power effective optimization solutions.


Discover the Qualifications:

  • Advanced Expertise:Master’s degree (or equivalent) in Operations Research, Computer Science, Engineering, or related field with a strong focus on optimization.
  • Proven Experience:5-7+ years in quantitative analytics, data modeling, or operations research, with deep knowledge of optimization techniques.
  • Technical Skills:Proficient in Python, SQL, and optimization libraries (e.g., PuLP, Gurobi, CPLEX).


Preferred Qualifications:

  • Leadership in Optimization:Experience leading complex optimization projects, mentoring teams, and managing cross-functional initiatives.
  • Machine Learning Integration:Expertise in integrating optimization with machine learning techniques (e.g., TensorFlow, PyTorch).
  • Cloud and MLOps:Familiarity with deploying and managing models on cloud platforms (AWS, GCP, Azure) and using MLOps tools (MLFlow, BentoML).
  • Ethical AI:Strong understanding of AI ethics in optimization and a commitment to continuous learning.


If you are looking for a fast paced progressive role, where you will be working with a very strong team of talented Data & AI professionals then Apply Now to be considered.

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.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

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.