This role is based in the United Kingdom and as such all normal working days must be carried out in the United Kingdom.
Join us as a Machine Learning Engineer
- You’ll lead, drive and embed the deployment, automation, maintenance and monitoring of machine learning models and algorithms to make sure that that they work effectively in a production environment
- We’ll look to you to understand the complex requirements and needs of business stakeholders, developing strong relationships, and how machine learning solutions can meet those needs to achieve business strategy goals
- This is a high-profile role that offers considerable exposure as well as the opportunity to make a significant impact
- You'll work from home some of the time, but you'll also spend a minimum of two days per week working from the office
This key role will see you working collaboratively with colleagues to productionise machine learning models including pipeline design and development, testing and deployment ensuring that the original intent and knowledge is carried over to production. You’ll create frameworks to ensure robust monitoring of machine learning models within production environment making sure these models are delivering expected quality and performance.
We’ll look to you to identify and communicate the actions needed to implement the function's strategy and business plan within the business area and explain the relationship to the broader organisation's mission, vision and values followed by motivating people to achieve local business goals.
You’ll also:
- Collaborate with colleagues to design and develop advanced machine learning products
- Codify and automate complex machine learning model productions including pipeline optimisation, tuning and fault finding
- Lead both direct reports and wider teams in an agile way within multi-disciplinary data and analytics teams to achieve agreed project and scrum outcomes
- Transform advanced data science prototypes and apply appropriate machine learning algorithms and tools
- Provide technical guidance and input on the design and implementation of machine learning algorithms and models
- Lead and deliver stakeholder engagement activities to develop effective project working relationships, ensuring that stakeholder needs and concerns are identified and met
We’re looking for someone with a strong academic background in a STEM discipline such as Mathematics, Physics, Engineering or Computer Science. You’ll have extensive experience building, testing, supporting and deploying advanced machine learning models into a production environment using modern CI or CD tools such as Git, TeamCity and CodeDeploy.
You’ll also have Financial Services knowledge, and the ability to identify wider business impact, risk and opportunities, making connections across key outputs and processes. We’ll expect you to have strong communication skills with the ability to proactively engage with a wide range of stakeholders.
Furthermore, you’ll need:
- Strong understanding of fraud and financial crime systems, including transaction monitoring, onboarding/KYC processes, and real-time risk decisioning, with the ability to apply this knowledge to analytical and machine learning solutions
- The ability to use data to solve business problems from hypotheses through to resolution
- Extensive experience with machine learning on large datasets
- A strong understanding of machine learning approaches and algorithms
- Experience using programming and scripting languages such as Python and Bash
- Experience in synthesising, translating and visualising data and insights for key stakeholders
