Data Analytics & Machine Learning Engineer
About StormHarvester
StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. We are the market leader in this space. At its core, StormHarvester's advanced anomaly detection system analyses data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions.
About the role
StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs.
Our products deliver on real-world issues, solving water company and industry problems with existing and new infrastructure that is critical to the environment, economy and everyday living.
We are primarily data driven with domain expertise delivering insights to water networks and assets using analytics, presentation, machine learning and AI that is SaaS and cloud based. We are building on our existing team to develop our existing products, and continue growing our customer offerings, base and revenues.
The ML & Data Services team is focused on maintaining and enhancing StormHarvester’s core ML capabilities, working with customers and other teams to apply new ML & data-driven solutions to meet customer’s needs, and developing processes to allow customers to get the most value out of their data.
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. It 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.
You will work within a team of 6-8, but will have ownership over individual projects, while also working within the larger engineering team to test and validate any features, fixes, or updates.
Job responsibilities
- Collaboration with stakeholders (e.g. wastewater domain experts) to understand contextual requirements of projects, to guide development of bespoke modelling approaches to address industry issues
- Designing scalable feature engineering and data transformation processes tailored to sewer data
- Development of predictive models using time series, geospatial and environmental sensor data
- Contributing to delivery process and development environments, including research and identifying areas of interest for further investigation
- Addressing bugs / changes, problem solving and support issues as part of wider engineering team
- Implementation, testing and delivery of designs / fixes as part of a continuous delivery mechanism through to live deployments.
Qualifications
- A third level qualification in Data Science, Computer Science, or a data / ML-driven equivalent;
- 3+ years of experience in Data Science, ML Engineering, Data Analytics, or a related speciality, or equivalent knowledge;
- Experience with Python (Pandas, Scikit-learn or equivalent);
- Experience with data exploration and visualisation;
- Strong presentation and communication skills;
- Willingness to engage and work with others as part of a team with shared direction;
- Strong work ethic with an understanding that this is a fast-growing company 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
- Experience with AWS services (or transferable cloud experience)
- Experience modelling time series data
- Familiarity with Geospatial (GIS) data
- Familiarity with MLOps principles
- Familiarity and experience with agile development in delivery
- Experience of Continuous Integration/Development and Tooling
- Experience using LLMs & other AI tools in a forward thinking and ethical way.
Benefits
- Comprehensive Private Medical insurance including dental and optical provision.
- Company pension scheme with 5% employer contribution and 5% employee contribution.
- Annual holidays of 24 days pro rata plus 1 day Birthday leave and 10 statutory holidays.
- Enhanced Maternity and Paternity Pay.
- Additional EV, Cycle, Tech & Home Scheme.
Join us in shaping the future of water and sustainability.
#J-18808-Ljbffr
Sign in
To continue your applicationor continue with email
By continuing you agree to our Terms & Privacy Policy.
