Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Wastewater Network Modeller - all grades

Advance TRS
London
8 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst (Wastewater Network)

Data Analyst (Wastewater Network)

Data Science Graduate

Data Engineering Technical Lead

Data Science Graduate

Data Analyst

Job Title: Wastewater Modelling SpecialistSalary: £35,000-£60,000 (dependent on experience)Location: South East England, near Haywards Heath (hybrid, ideally 2-3 days per week in office, with flexibility for senior/principal-level candidates)Type: PermanentAbout the Role:This role is an exciting opportunity to work at the intersection of machine learning, data science, and wastewater modelling. You will contribute to groundbreaking projects in optimisation, digital transformation, automation, and real-time modelling, leveraging state-of-the-art tools and methodologies.About the Client:Our client is a UK-based team specialising in innovative modelling services that set them apart from other consultants. Their focus includes optimisation, digital transformation, automation, and cutting-edge water quality and real-time modelling techniques. This role offers you a chance to join a collaborative environment with training and mentorship from one of the UK's leading experts in hydraulics and hydraulic modelling.Key Responsibilities:Develop machine learning, AI, and data analytics solutions to support wastewater modelling.Utilise programming languages such as Ruby, FME, and Python to create robust modelling tools.Work with industry-standard tools like InfoWorks ICM and ArcGIS.Engage in model audits, 2D and water quality modelling, and optimisation projects.Participate in digital transformation initiatives to drive innovation across the industry.What Our Client is Looking For:Expertise in machine learning, AI, data science, and data analytics.Proficiency in programming languages, particularly Ruby, FME, and Python.Experience in wastewater modelling and familiarity with InfoWorks ICM.A keen interest in innovation, digital transformation, and optimisation.A collaborative and flexible approach to work.What Our Client Offers:Comprehensive training in key areas, including Optimizer software, ArcGIS, water quality modelling, and US hydrology.Mentorship from one of the UK's leading experts in hydraulics and hydraulic modelling.Company-funded travel opportunities to the USA for collaboration, conferences, and additional training.A chance to work on specialised modelling services, setting you apart in the industry.Eligibility:Applicants must be eligible to work in the UK and able to commit to a hybrid working arrangement with 2-3 days per week in the office (flexibility provided for senior/principal-level candidates).Opportunity for Growth:This role offers unmatched opportunities to expand your expertise in machine learning, data analytics, and wastewater modelling. With access to world-class training and a focus on innovation, you'll play a pivotal role in shaping the future of the industry.We are an equal opportunity employer and value diversity in our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.TPBN1_UKTJ

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.