Analytics Engineer

Location: Guernsey, Haywards Heath, Home Office (Remote) or Manchester

Salary: £50,000 - £70,000 - depending on experience

Department: Technology and Data

We’re First Central Insurance & Technology Group (First Central for short), an innovative, market-leading insurance company. We protect the things customers love so they can get on with what matters to them in life.

Data drives us. It fuels our outstanding distribution, finance, technology and legal services. Our underwriting skills are built on data expertise; it creates the insights we need to give the right cover to the right customers at the right price. But, it’s the people inside and outside our business that power us. They make us stand out, help us succeed. We’re ambitious. We’re growing. We’ve won awards.

Are you looking to advance your career in a dynamic and fast-paced environment? We’re seeking anAI & Machine Learning Engineerto join our innovative technology and data teams.

Working as an AI & Machine Learning Engineer you’ll be responsible for understanding and answering complex business questions using advanced data and analytics techniques. You’ll be technically proficient in the end-to-end AI and machine learning model development lifecycle, with experience of prompt engineering, and a keen interest in keeping up with the rapidly evolving industry trends.

Your role will include working closely with business stakeholders to create hypotheses, design and evaluate experiments and implement solutions that unlock significant business value in collaboration with teams such as Data Engineering, Machine Learning Operations (MLOps), Architecture, and Software Development. You’ll also proactively identify opportunities, providing the level of advanced analytics support needed for the problem and will provide technical thought leadership regarding the ethical, sustainable and scalable use of AI and machine learning solutions.

Could you fit the bill? We're big on working flexibly - you'll spend most of your time working from home, with occasional visits to the office. But of course, it’s your choice - if you prefer to be in the office more - that's good with us too.

Core skills we’re looking for to succeed in the role:

• Innovative Experiment Design:You’ll turn complex business questions into innovative, well-designed experiments that prove value.
• Advanced Analytics Implementation:You’ll identify opportunities for advanced analytics such as Machine Learning, AI, Generative AI, and Data Science, and implement them within an Agile framework.
• Technical Proficiency:You’ll be able to build models and AI Agents in tools such as Microsoft Azure, Data Bricks, Azure Open AI, and using prompt engineering.
• Collaborative Communication:You’ll possess strong collaboration and communication skills to ensure both technical and non-technical team members understand the cutting-edge solutions.

What’s involved:

• You’ll work closely with business stakeholders to identify and shape complex questions into well-designed experiments that prove value.
• You’ll perform rigorous experimentation using a wide variety of data and analytics techniques appropriate to the problem statement.
• You’ll proactively identify opportunities to use advanced analytics techniques including machine learning, AI and Generative AI modelling, and data science.
• You’ll support the operationalisation of machine learning and AI models by developing according to standards set by the MLOps framework.
• You’ll assist in the design and implementation of data pipelines and engineering infrastructure to embed scaled machine learning solutions.
• You’ll support the implementation of AI, GenAI and Machine Learning on cloud (Experience with Azure, Azure ML, Azure Open AI and Databricks is advantageous).
• You’ll provide technical thought-leadership to the organisation around the ethical, sustainable and scalable use of AI and machine learning solutions.
• You’ll actively engage with, and potentially run, business wide hackathons to support innovation.
• You’ll engage in group discussions on system design and architecture, sharing knowledge with the wider engineering community.
• You’ll collaborate closely with data scientists, data engineers, MLOps engineers, architects, and the software development team when developing solutions.
• You’ll liaise with stakeholders across the business to ensure ML is being used to improve strategic business decisions and identify new areas for improvements.
• You’ll adhere to the Group Code of Conduct and Fitness and Propriety policies, Company Policies, Values, guidelines, and other relevant standards/ regulations at all times.

Experience & knowledge:

• Experience of designing data experiments using scientific methodology.
• Proven ability to identify and apply a relevant set of analytics techniques to a business problem, including simple analysis, visualisation, advanced analysis, and modelling.
• Experience of developing production ML systems, incorporating MLOps best practices to ensure long-term value delivery and minimal risk.
• Knowledge of AI and Generative AI implementation and the ability to identify opportunities for this capability to benefit the business.
• Handling large volumes of varied data in various stages of the data pipeline, from ingestion to processing.
• Proven experience with feature stores, using them for both offline model development and online production usage.
• Building integrations between cloud-based systems using APIs, specifically within the Azure environment.
• Practical knowledge of agile methodologies applied in a data science and machine learning environment.
• Designing, implementing, and maintaining data software development lifecycles, with a focus on continuous integration and deployment (CI/CD).
• Demonstratable expertise in machine learning methodology, best practices, and frameworks.
• Understanding of microservices architecture, RESTful API design, development, and integration.
• Experience with Azure and Databricks is required.
• Basic understanding of networking concepts within Azure.
• Familiarity with Docker and Kubernetes is advantageous.
• Experience within financial/insurance services industry is advantageous.

Skills:

• Strong understanding of Microsoft Azure and Databricks (Azure ML, Azure Open AI, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory).
• Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc.
• Excellent communication skills, both verbal and written.
• Ability to explain technical concepts to a non-technical audience.
• Ability to influence stakeholders and broaden others thinking in the area of advanced analytics.
• Strong time management and organisation skills.
• Ability to diagnose and troubleshoot problems quickly, both technical and non-technical.
• Excellent problem-solving and analytic skills.

Behaviours:

• Embrace, embed and incorporate the company values.
• Self-motivated and enthusiastic.
• An organised and proactive approach.
• Ability to work on own initiative and as part of a team.
• A flexible approach and positive attitude.
• Strives to drive business improvements to contribute to the success of the business.

Ready to make a positive impact? Apply now and be part of something big!

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