Data Analytics & Machine Learning Engineer LOCATION: Belfast, On Site
Office Location: Belfast
Working Arrangement: On Site
About StormHarvester
Our products deliver on real-world issues in 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.
About the role
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 role is ideal for a Data Scientist or ML Engineer who wants to work on impactful real-world problems and take ownership of your work. You’ll be part of a fast-moving, collaborative team with room to develop your skills in applying novel ML & AI techniques.
We are seeking a Machine Learning Engineer to contribute to the development and deployment of ML-driven features in our core wastewater network platform focusing on predicting sewer behaviour. You will work within the Data & Modelling engineering team with a focus on improving our existing ML processes and designing and integrating new data-driven strategies into existing products to help add insight for our customers. This role will be involved with (and lead) the development of a new ML-driven feature from ideation to proof of concept to deployment to integration with the product. This will involve:
- Gaining an understanding of the domain and existing StormHarvester product
- Exploratory data analysis and visualisation
- Conceptualising solutions and presenting to internal and external stakeholders
- Helping define and develop the strategy to deploy the approach at scale
- Integration of solutions into the product
Job requirements
- A third level qualification in Data Science, Computer Science, or a data/ML driven equivalent.
- 5+ years of experience in Data Science, ML Engineering, Data Analytics, or a related speciality.
- 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 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.
- Can-do, problem-solving mindset.
- 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
Key Responsibilities
- Collaboration with wastewater domain experts to guide bespoke modelling approaches to address industry issues.
- Development of predictive models using time series, geospatial and environmental sensor data.
- Designing scalable feature engineering and data transformation processes tailored to sewer data.
- 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 engineering team.
Job 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.
- Car parking at the office.
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