Data Analytics and Machine Learning Engineer

About StormHarvester:

Our products solve problems for water companies and the industry in the real world. They are critical to the environment, economy, and daily life. We use data, analytics, machine learning, and AI to deliver insights to water networks and assets through SAAS and cloud-based services. Our team is expanding to improve our existing products, grow our customer base, and increase revenue.

About the role:

You will work within the R&D Services team with a strong focus on bespoke client projects, 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 customers,  
• Integration into the product. 

You’ll work within a team of 4-6 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.
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

• Build required product and custom features while seeking to maximise reuse and productisation of 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. 
• Planning for future developments as part of a team, including contributions to team structures, roles and requirements with an awareness of all existing and future customers in mind. 

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 

 Essential criteria:

• 2 – 5 years of experience and familiarity with development and delivery including and involving data analytics, machine learning models and AI principles and application in implementation and practical delivery. 
• A third level qualification in Computer Science, Software Engineering, Data Science or other related discipline. 
• Experienced in Python development and tooling including Pandas, Scikit-learn or equivalent. 
• 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. 
• Can do, problem solving mindset. 
• Curious and willing to onward develop and learn in ML/AI area. 

 Desirable criteria:

• 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