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

Apply Now

▷ High Salary: Data Scientist...

Harnham
London
2 days ago
Create job alert

Job Description

Contract Opportunity: Lead Data Scientist (Image-Based Predictive Modelling)

Location: London / Hybrid / Remote
Day Rate: Up to £600/day (Inside or Outside IR35)
Contract Length: Initial 5 weeks (very strong extension potential)
Start Date: Within 1-2 weeks
Industry: Financial Services (Marketing Analytics Project)
Interview Slots Available This Week - Fast Turnaround

About the Company

Join a specialist data and analytics consultancy working with major financial services organisations. You'll be part of a high-performing, agile squad that owns delivery end-to-end. The environment is innovative, outcome-focused, and ideal for individuals who enjoy solving commercially impactful problems with autonomy.

The Opportunity

This is a hands-on Lead Data Scientist role where you'll take ownership of an existing project focused on predicting customer engagement from marketing images. Your goal: build and deploy a model that forecasts click-through rates and explains why certain images drive better performance.

What You'll Be Doing

✅ Build and refine a predictive model using image data & historical engagement metrics
✅ Identify which image characteristics (colour, objects, themes) influence customer behaviour
✅ Implement explainability (e.g. SHAP, feature importance)
✅ Build a simple internal UI (Dash, Streamlit, or Flask) for stakeholders to explore insights
✅ Present findings and guide technical decision-making internally
✅ Enable deployment teams to operationalise your solution

What Success Looks Like

By the end of the initial engagement you will have delivered:

  • A working predictive model
  • Clear explainability on what drives user clicks
  • A functional internal tool for non-technical stakeholders
  • Documentation and guidance for productionisation

    Required Skills

    Must-Have:

  • Expert-level Python (Pandas, modelling libraries such as Scikit-learn)

  • SQL

  • AWS cloud experience

  • Proven end-to-end ownership of data science solutions

  • Model explainability (SHAP, LIME, feature importance)

  • Ability to build simple dashboards or web apps (Streamlit, Dash, or Flask)

    Nice-to-Have:

  • Experience working with image data

  • Exposure to marketing analytics or customer behaviour modelling

    Desired Skills and Experience
    Key Experience
    Built an image-based predictive model to forecast marketing click-through rates
    Applied explainability techniques (SHAP, feature importance) to identify visual drivers of customer engagement
    Developed a Python-based dashboard (Dash/Streamlit) for internal stakeholders to explore insights in real time
    Led end-to-end delivery from data ingestion to deployment on AWS
    Collaborated within an agile squad to accelerate delivery for a major financial services programme

Related Jobs

View all jobs

▷ (High Salary) Machine Learning Engineering Lead...

▷ (Only 24h Left) Marketing Data Analyst...

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 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.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.