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

Apply Now

Senior Software and Data Engineer

Portman Scott
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist, Payments Foundation Models

Senior Data Scientist, Payments Foundation Models

Head of Data Science Technology (Product, Engineering, Design) · London ·

Senior Data Scientist

Data Scientist

Machine Learning Engineer (Databricks)

Permanent

Salary - £80,000 - £95,000 p/a + benefits

Remote, UK

Data plays a crucial role in guiding my clients investment decisions and managing risk. Their analytics provide insights that help them evaluate growth potential and performance, while separately allowing them to support their clients. Through a strong data-driven approach, they enable entrepreneurs to make impactful, data-informed decisions that support sustained growth.

Tasks

I am seeking a resourceful and adaptable engineer with 3-5 years of experience and a strong foundation in computer science, data science, and mathematics. This role covers analytics, platform, architecture, and data engineering and is ideal for a versatile individual eager to take a hands-on role with the autonomy to drive projects and make significant contributions as we develop our capabilities from the ground up.

Requirements

Qualifications:

  • Education:BSc, MSc, or PhD in Computer Science, Data Science, Applied Mathematics, or a related field.
  • Experience:3-5 years in a FinTech, data science, or data engineering role with a strong focus on independent project ownership and end-to-end solution development. Experience in a start-up environment is desirable.

Technical Skills:

  • Advanced skills in Python, Django, or similar programming languages, with a strong command of data processing and machine learning libraries.
  • MUST HAVE- Proficiency in data visualisation tools (e.g., Matplotlib, Plotly, Tableau) for effective data presentation.
  • Familiarity with cloud services (preferably Google Cloud) and an ability to leverage available resources creatively.

If you meet these qualifications and are excited about the opportunity to join our team, we’d love to hear from you!



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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.