Data Scientist / Machine Learning Engineer (KTP Associate)

at  Manchester Metropolitan University

Position: Data Scientist / Machine Learning Engineer (KTP Associate)
Based at: Pumpflow, Manchester
Salary: Up to £35,000, depending on experience

QUALIFICATION WE REQUIRE:

A first-class BSc in machine learning, data science, computer science, artificial intelligence, statistics, mathematics, physics, or a related, computational science discipline. A postgraduate degree and/or substantial related work experience are highly desirable.

APPLICATION REQUIREMENTS:

• Fluency with a machine learning/data science environment and ecosystem such as Python with Jupyter Lab and essential packages like numpy, pandas, matplotlib, and scikit-learn.
• Experience with processing and analysing tabular, timeseries, and signal data.
• Good theoretical and practical skills in selection, training, evaluating, diagnosing, deployment, and monitoring of machine learning algorithms for classification and regression tasks.
• Excellent oral and written communication skills; ability to disseminate complex concepts in a clear manner to stakeholders with varying degree of technical and scientific background, as well as to produce publications (e.g., research papers) at international level.
• Ability to lead a technical project by working both independently and collaboratively, with good decision making and workload/time management skills.

An exciting opportunity has become available for a recent graduate to work full time 18-month Knowledge Transfer Partnership (KTP) data scientist/machine learning engineer position in a project to develop a machine learning based solution, combined with timeseries and signal processing techniques, to forecasting dynamic characteristics of centrifugal pumps in large-scale industrial settings. The goal is to use machine learning models to support control systems for more sustainable and cost/resource-efficient operation of the equipment. The project is a spin-off of a short-term Greater Manchester AI Foundry Technical Assist Project. It is likely to have a measurable impact in sustainability and to include some key and well-established stakeholders (e.g., UK’s Environmental Agency).
Employed and supported by an academic team from the University, you will be based at Pumpflow’s premises in Manchester. The post is primarily based at Pumpflow’s sites, but with possibility of flexible work arrangements.
To find out more about Pumpflow, go to https://www.pumpflow.net/.