Data Analytics and Machine Learning Engineer

StormHarvester is a software provider working with wastewater utility companies.Foun...

Data Analytics and Machine Learning EngineerData Analytics and Machine Learning Engineer

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

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