Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Lead Data Scientist, Machine Learning Engineer 2025- UK

Aimpoint Digital
London
2 months ago
Applications closed

Related Jobs

View all jobs

Lead Machine Learning Engineer - Databricks experience

Lead Machine Learning Engineer - Databricks experience

Lead Machine Learning Engineer - Databricks experience

Lead Machine Learning Engineer - Databricks experience

Lead Machine Learning Engineer - Databricks experience

Lead Machine Learning Engineer - Databricks experience

Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This position is within our decision sciences practice which focuses on delivering solutions via machine learning and statistical modelling.

What you will do

As a part of Aimpoint Digital, you will focus on enabling clients to get the most out of their data. You will work with all levels of the client organization to build value driving solutions that extract insights and then train them on how to manage and maintain these solutions. Typical solutions will utilize machine learning, artificial intelligence, statistical analysis, automation, optimization, and/or data visualizations. As a Lead Data Scientist, you will be expected to work independently on client engagements, take part in the development of our practice, aid in business development, and contribute innovative ideas and initiatives to our company. As a Lead Data Scientist you will:

  • Become a trusted advisor working with clients to design end-to-end analytical solutions
  • Work independently to solve complex data science use-cases across various industries
  • Design and develop feature engineering pipelines, build ML & AI infrastructure, deploy models, and orchestrate advanced analytical insights
  • Write code in SQL, Python, and Spark following software engineering best practices
  • Collaborate with stakeholders and customers to ensure successful project delivery

Who we are looking for

We are looking for collaborative individuals who want to drive value, work in a fast-paced environment, and solve real business problems. You are a coder who writes efficient and optimized code leveraging key Databricks features. You are a problem-solver who can deliver simple, elegant solutions as well as cutting-edge solutions that, regardless of complexity, your clients can understand, implement, and maintain. You genuinely think about the end-to-end machine learning pipeline as you generate robust solutions. You are both a teacher and a student as we enable our clients, upskill our teammates, and learn from one another. You want to drive impact for your clients and do so through thoughtfulness, prioritization, and seeing a solution through from brainstorming to deployment. In particular you have these traits:

  • Degree in Computer Science, Engineering, Mathematics, or equivalent experience.
  • Experience with building high quality Data Science models to solve a client's business problems
  • Experience with managing stakeholders and collaborating with customers
  • Strong written and verbal communication skills required
  • Ability to manage an individual workstream independently
  • 3+ years of experience developing and deploying ML models in any platform (Azure, AWS, GCP, Databricks etc.)
  • Ability to apply data science methodologies and principles to real life projects
  • Expertise in software engineering concepts and best practices
  • Self-starter with excellent communication skills, able to work independently, and lead projects, initiatives, and/or people
  • Willingness to travel.

Want to stand out?

  • Consulting Experience
  • Databricks Machine Learning Associate or Machine Learning Professional Certification.
  • Familiarity with traditional machine learning tools such as Python, SKLearn, XGBoost, SparkML, etc.
  • Experience with deep learning frameworks like TensorFlow or PyTorch.
  • Knowledge of ML model deployment options (e.g., Azure Functions, FastAPI, Kubernetes) for real-time and batch processing.
  • Experience with CI/CD pipelines (e.g., DevOps pipelines, Git actions).
  • Knowledge of infrastructure as code (e.g., Terraform, ARM Template, Databricks Asset Bundles).
  • Understanding of advanced machine learning techniques, including graph-based processing, computer vision, natural language processing, and simulation modeling.
  • Experience with generative AI and LLMs, such as LLamaIndex and LangChain
  • Understanding of MLOps or LLMOps.
  • Familiarity with Agile methodologies, preferably Scrum

We are actively seeking candidates for full-time, remote work within the UK.


#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.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

Why Now Is the Perfect Time to Launch Your Career in Machine Learning: The UK's Intelligence Revolution

The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.