At a Glance
- Tasks: Develop predictive models and integrate data-driven strategies for wastewater networks.
- Company: StormHarvester provides innovative software solutions for water utilities using data and machine learning.
- Benefits: Enjoy free parking, private medical insurance, 24+ days annual leave, and an electric vehicle scheme.
- Other info: This is a hybrid role based in Northern Ireland with opportunities for rapid growth.
- Why this job: Make a real impact on the environment while working in a dynamic, collaborative team.
- Qualifications: 3+ years in data analytics and machine learning; Python experience required.
The predicted salary is between 36000 - 60000 £ per year.
LOCATION: NI / Hybrid
About StormHarvester:
Our software solutions solve problems for water utilities. We use data, analytics, and machine learning to deliver insights to water networks and assets through SAAS and cloud-based services. We are expanding our team to improve our existing products and develop new modules.
About the role:
ML-driven features in our core wastewater network platform focusing on predicting sewer behaviour. You will work within the Data & Modelling team with a focus on improving our existing ML processes, aiming to understand behaviour in the water network and designing and integrating new data-driven strategies into existing products to help add insight for our customers.
The role will involve:
- Exploratory data analysis and visualisation
- Conceptualising solutions and presenting to internal stakeholders and external customers
- Integration of solutions into the product
You’ll work within the Data & Modelling team of 8-10 people but have ownership over individual projects, while also working within the larger development team to test and validate any features, fixes or updates. You’ll have opportunities to explore different strategies in order to identify the best approach. The models you design will be used directly by water utilities to predict and prevent real-time events, reducing harm to the environment.
This is a pragmatic and delivery-focused role in the use of data, analytics, and ML to deliver predictive outcomes for StormHarvester customers as part of our product. This will involve working with customer data, understanding and appreciating the underlying domain, carrying out analysis, and integrating or developing new techniques for implementation and delivery as part of our product offerings. This includes feature engineering, applying varying models, testing, and validation, and best practices for use for customers.
Responsibilities:
- Development of predictive models using time series, geospatial and environmental sensor data.
- Designing scalable feature engineering and data transformation processes tailored to sewer data.
- Collaboration with wastewater domain experts to guide bespoke modelling approaches to address industry issues.
- Build required product and custom features while seeking to maximise reuse of existing code and features.
- Engaging with customers to understand contextual requirements of projects, present findings and lead integration into StormHarvester product.
- Contribute to delivery process and development environments, including research and identifying areas of interest for further investigation.
- Implementation, test and delivery of designs/fixes as part of a continuous delivery mechanism through to live deployments.
- Addressing bugs/changes, problem solving and support issues as part of wider team.
- Preparing and presenting potential delivery options including estimating, costing and prioritising.
To do the role effectively, you will need to become familiar with:
- The StormHarvester product and internal tools for understanding and predicting behaviours
- The sewer network, the components, and processes involved including geospatial connectivity
- StormHarvester customers and SLAs
- Current use of live predictive models to alert and raise alarms for sites and customers
- 3+ years of experience involving data analytics, machine learning models and AI principles and application in implementation and practical delivery.
- Experienced in Python development and tooling including Pandas, Scikit-learn or equivalent.
- A third level qualification in Computer Science, Software Engineering, Data Science or other related discipline.
- Experience with data exploration and visualisation.
- A theoretical and practical foundation of core analytics and machine learning principles and experience working with large scale data.
- Strong presentation and communication skills.
- Willingness to engage and work with others as part of team with shared direction.
- Strong work ethic with an understanding that this is a start-up with lots of opportunities to make improvements and to move quickly.
- Ability to review and provide feedback as needed to other teams on areas for improvements and updates.
- Passionate about work, output and quality.
- Curious and willing to onward develop and learn in ML/AI area.
Desirable Criteria
Benefits:
- Familiarity with MLOps principles
- Familiarity with Geospatial (GIS) data
- Familiarity and experience with agile development in delivery
- Experience in Automation/Testing frameworks
- Experience of Continuous Integration/Development and Tooling
- Experience of test/deployment automation
- Experience of AWS services
- Free parking at our Belfast office
- Private medical and dental insurance
- 24 days+ annual leave
- Electric vehicle scheme
Apply here
A leading analytics provider in the wastewater space. Our insight helps wastewater utilities better manage their networks.
UK Tel: 0800 088 6560
ROI Tel: 01 697 1500
Data Analytics and Machine Learning Engineer in Belfast employer: StormHarvester
At StormHarvester, we pride ourselves on being an excellent employer by fostering a collaborative and innovative work culture that empowers our employees to take ownership of their projects. Located in a vibrant area, we offer competitive benefits, continuous learning opportunities, and the chance to make a meaningful impact in the water industry through cutting-edge data analytics and machine learning solutions. Join us to be part of a dedicated team that values your contributions and supports your professional growth.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analytics and Machine Learning Engineer in Belfast
✨Tip Number 1
Familiarise yourself with the StormHarvester product and its functionalities. Understanding how our software solutions work will not only help you during the interview but also demonstrate your genuine interest in the role.
✨Tip Number 2
Brush up on your Python skills, especially with libraries like Pandas and Scikit-learn. Being able to discuss specific projects where you've applied these tools will set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your experience with predictive modelling and data analysis. Think of examples where you've successfully implemented machine learning models and be ready to explain your thought process and outcomes.
✨Tip Number 4
Showcase your communication skills by preparing to present complex data insights clearly. Since you'll be engaging with both internal teams and external customers, being able to convey technical information effectively is crucial.
We think you need these skills to ace Data Analytics and Machine Learning Engineer in Belfast
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in data analytics and machine learning. Focus on projects where you've developed predictive models or worked with large datasets, especially in the context of environmental or geospatial data.
Craft a Compelling Cover Letter:In your cover letter, express your passion for using data to solve real-world problems, particularly in the wastewater sector. Mention specific skills that align with the job description, such as Python development and experience with tools like Pandas and Scikit-learn.
Showcase Your Projects:If you have any relevant projects or case studies, include them in your application. This could be links to GitHub repositories or detailed descriptions of your work that demonstrate your ability to apply machine learning principles effectively.
Prepare for Technical Questions:Anticipate technical questions related to data analytics and machine learning during the interview process. Brush up on your knowledge of time series analysis, feature engineering, and model validation techniques, as these are crucial for the role.
How to prepare for a job interview at StormHarvester
✨Understand the Company and Its Products
Before your interview, make sure to research StormHarvester thoroughly. Familiarise yourself with their software solutions, especially how they use data analytics and machine learning in wastewater management. This knowledge will help you demonstrate your genuine interest in the role and the company.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, data analytics, and machine learning models. Bring examples of past projects where you've applied these skills, particularly in predictive modelling or feature engineering. Highlight any relevant tools you've used, such as Pandas or Scikit-learn.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities. Think about challenges you've encountered in previous roles and how you overcame them, especially in relation to data analysis or model implementation. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Demonstrate Communication Skills
Since the role involves presenting findings to stakeholders and customers, practice articulating complex technical concepts in a clear and concise manner. Be ready to explain your thought process and how you would engage with non-technical team members or clients to ensure understanding.
