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- Tasks: Join us to develop cutting-edge wastewater models using AI and data analytics.
- Company: Be part of a UK-based team known for innovative modelling services in the water sector.
- Benefits: Enjoy hybrid work flexibility, training, and mentorship from industry experts.
- Why this job: Work on groundbreaking projects that make a real impact in digital transformation and automation.
- Qualifications: Experience with programming languages like Ruby, FME, and Python is essential.
- Other info: Ideal for those passionate about machine learning and environmental sustainability.
The predicted salary is between 35000 - 60000 £ per year.
Job Title: Wastewater Modelling Specialist
Salary: £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: Permanent
About the Role:
This role is an exciting opportunity to work at the intersection of machine learning, data science, and wastewater modelling. Yo…
Wastewater Network Modeller - all grades employer: Advance TRS
Contact Detail:
Advance TRS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Wastewater Network Modeller - all grades
✨Tip Number 1
Familiarize yourself with the latest trends in machine learning and data science as they relate to wastewater modelling. This knowledge will not only help you stand out but also demonstrate your commitment to staying at the forefront of the industry.
✨Tip Number 2
Make sure to showcase any experience you have with programming languages like Ruby, FME, and Python. Highlighting specific projects where you've utilized these tools can give you an edge over other candidates.
✨Tip Number 3
Engage with online communities or forums related to wastewater modelling and digital transformation. Networking with professionals in the field can provide valuable insights and potentially lead to referrals.
✨Tip Number 4
Research the company’s recent projects and innovations in wastewater modelling. Being able to discuss their work during an interview shows genuine interest and can set you apart from other applicants.
We think you need these skills to ace Wastewater Network Modeller - all grades
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities and requirements. Highlight your experience with machine learning, data science, and programming languages like Ruby, FME, and Python in your application.
Tailor Your CV: Customize your CV to reflect relevant experience in wastewater modelling and any projects that demonstrate your skills in optimisation and digital transformation. Use specific examples to showcase your expertise.
Craft a Compelling Cover Letter: Write a cover letter that connects your background to the role. Emphasize your passion for innovative modelling services and how you can contribute to the client's goals. Mention your willingness to work in a hybrid environment.
Highlight Collaborative Experience: Since the role involves working in a collaborative environment, be sure to mention any previous teamwork experiences. Discuss how you have successfully collaborated on projects and learned from mentors in your field.
How to prepare for a job interview at Advance TRS
✨Showcase Your Technical Skills
Be prepared to discuss your experience with programming languages like Ruby, FME, and Python. Highlight specific projects where you've developed machine learning or data analytics solutions related to wastewater modelling.
✨Understand the Industry Tools
Familiarize yourself with industry-standard tools such as InfoWorks ICM and ArcGIS. Be ready to explain how you've used these tools in past projects and how they can be applied to the role you're interviewing for.
✨Demonstrate Problem-Solving Abilities
Prepare examples of how you've tackled complex modelling challenges in the past. Discuss your approach to optimisation and digital transformation, showcasing your analytical thinking and creativity.
✨Emphasize Collaboration and Learning
Since this role involves working in a collaborative environment, express your enthusiasm for teamwork and mentorship. Share experiences where you've successfully collaborated with others and how you value continuous learning in your career.
