Jobs at CTM Data & Electrical

Create persuasive, on-brand copy across advertising, CRM, digital, web, social, video, and campaign communications. Develop creative concepts with designers and stakeholders, adapt messaging for varied audiences and channels, champion brand tone of voice, and use customer insight, testing, and performance data to improve effectiveness. Present recommendations and collaborate with marketing, product, legal, and compliance teams to deliver clear, engaging communications in regulated or complex environments.

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.

Leads complex security engineering initiatives, establishes technical strategy and architecture, develops security roadmaps, and embeds security-by-design across cloud, distributed, microservices, and AI-enabled environments. Acts as a security subject matter expert, mentors engineers, evaluates new security capabilities, and supports complex cyber incident and vulnerability response. Requires broad information security expertise, strong stakeholder influence, cloud experience, and technical leadership.

Perform product and behavioural analysis (funnel, cohort, segmentation), define KPIs, run A/B tests, build dashboards, partner with Product and Analytics Engineering, and apply AI/ML techniques to drive product decisions and experimentation.

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.

Design, build and maintain scalable automated test frameworks and reusable test solutions. Create API, integration, end-to-end and non-functional tests integrated into CI/CD. Collaborate with engineers, product and architects to embed shift-left testing and quality by design, contribute to tooling, perform root-cause analysis, participate in code reviews and continuously evaluate tools to improve quality engineering practices.

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.

Provide first-line governance for AI systems across lifecycle: assess and test models (including generative and agentic systems), produce technical risk reports and metrics, advise on 'License to Operate' decisions, consult on high-risk system design, and partner with Data Science, ML Engineering, Risk & Compliance to evolve governance standards.

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.

Design, operate, and optimise highly available database and storage systems to improve reliability, performance, scalability and observability. Lead platform improvements, automate operations, support data pipelines, participate in incident response and root cause analysis, and collaborate with engineering and data teams to evolve platform capabilities.

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.

Support development, execution and optimisation of multi-channel media campaigns (AV, social, digital, OOH). Coordinate with agencies and stakeholders, monitor performance against KPIs, prepare reports/dashboards, manage budgets, implement testing and learning, and recommend optimisations to improve media effectiveness and ROMI.