Jobs at CTM Data & Electrical

Lead the implementation and continuous improvement of enterprise Data Loss Prevention capabilities. Configure and optimize Netskope, Microsoft Purview, Wiz, and Kiteworks; manage data discovery, classification, labelling, secure file sharing, and DLP alerts. Investigate incidents, produce audit reporting, maintain security standards, and partner with cybersecurity, legal, compliance, privacy, and technology teams. Support automation, vendor management, regulatory compliance, and broader data security improvements.

Sets technical direction for data and AI capabilities, leads large-scale production solutions, establishes engineering standards and reusable frameworks, improves AI monitoring and evaluation, partners with senior stakeholders, mentors engineers, and supports responsible AI adoption across the organization.

Own the App Store Optimisation strategy, improving app visibility, web-to-app conversion, and install growth. Lead data-driven A/B testing, optimise app listings through keyword and creative testing, monitor competitors and app performance, and use analytics and customer insights to improve acquisition. Collaborate with Product, UX, SEO, Content, and App Marketing teams while influencing stakeholders and delivering measurable growth outcomes.

Lead and grow a team of ML engineers to build and operate production ML and LLM systems—real-time inference APIs, batch data products, and agentic AI—ensuring deployment, monitoring, CI/CD, reproducibility, and measurable business impact.

Configure, customize, and improve Oracle Cloud HCM and related HR technology platforms. Serve as the HR systems technical subject matter expert, supporting troubleshooting, impact assessments, testing, releases, integrations, and vendor coordination. Administer Oracle HCM, Recruiting Cloud, BI, security, and reporting capabilities while identifying automation and process-improvement opportunities. Partner with HR and IT stakeholders to deliver reliable technology solutions and improve the colleague experience.

Own technical outcomes for scalable product platforms and shared capabilities. Define architectures, technical strategies, engineering standards, APIs, services, and integration patterns across multiple teams. Lead technical discovery, simplify the technology estate, improve platform adoption, and make strategic decisions balancing value, quality, scalability, cost, and risk. Champion agentic Spec Driven Development and AI-assisted tooling, evaluate emerging technologies, mentor senior engineers, and influence organization-wide engineering direction.

Lead complex data and analytics workstreams while designing scalable solutions with SQL, dbt, Python, and modern data platforms. Drive data modeling, testing, CI/CD, documentation, reliability, and incident resolution. Partner with Product, Analytics, Technology, and Data Platform teams to deliver trusted data products, reporting, and commercial insights. Mentor engineers, delegate effectively, influence stakeholders, and help shape technical strategy and roadmaps.

Lead design and evolution of the product operating model, implement AI-enabled workflows and tooling, define operational standards across product lifecycle, improve processes and knowledge management, drive adoption of modern product practices, and partner cross-functionally to enable faster, insight-driven product delivery.

Design, implement, test, secure, and maintain backend services for commercial journeys. Collaborate with product and cross-functional engineering teams, embed testing and security standards, contribute to CI/CD pipelines, and participate in engineering communities and agile delivery practices.

Lead high‑impact AI and decisioning projects from discovery through production. Define technical roadmaps, design and validate models (including causal/experimentation), partner with engineering to productionise services with monitoring and governance, mentor data scientists, and promote responsible AI practices and platform adoption.

Own end-to-end delivery of production ML and LLM-powered systems: design and build training/deployment pipelines, package and deploy models, implement monitoring for performance and drift, support batch and real-time workloads, evolve internal ML platform and tooling, promote best practices, and provide technical leadership and mentoring across data science and engineering teams.

Build, deploy, and maintain production ML and AI systems: model packaging, lifecycle automation, monitoring, batch and real-time workloads, and platform improvements while collaborating with data scientists, engineers, and product teams.

Lead a data science team building always-on predictive models and pipelines for an AI platform. Own model lifecycle: production deployment, monitoring, drift detection, retraining, and measurable business outcomes. Provide technical leadership, code reviews, architecture decisions, and stakeholder collaboration. Hire and mentor data scientists, champion responsible and auditable AI, and adopt ML platform tooling (MLflow, model registries, Databricks) and LLM/RAG approaches where appropriate.

Lead design and deployment of ML models and pipelines for the AI platform. Translate business problems into measurable ML solutions, design experiments and A/B tests, and own model performance, monitoring, degradation detection and retraining. Champion responsible, explainable AI in a regulated financial context, choose between classical ML, LLMs and agentic approaches, collaborate with ML engineering, product and commercial teams, and mentor junior data scientists.

Define and lead LLM discovery and optimisation strategy across SEO and AI-driven platforms. Monitor generative AI/search developments, translate trends to strategy, run measurement and experimentation linking visibility to business outcomes, and partner cross-functionally to embed AI discovery insights. Specify technical, content and authority signals for generative responses and establish governance, best practices and capability-building.

Create and present short-form football content as the face of Compare the Market’s EFL partnership. Attend EFL matches nationwide, engage fans, manage community interaction, and showcase club traditions through a recurring social media series. The role requires regular travel, confident on-camera presenting, strong editorial judgment, brand alignment, and the ability to work within approval processes while maintaining an authentic voice.