Machine Learning Engineer - Remote

Overview

This role will take full ownership of all existing ML assets at UNiDAYS, driving their improvement and optimization, while leading the development of future ML innovations that benefit UNiDAYS members, partners and business performance. As the sole ML expert at UNiDAYS, you will work closely with analytics, data engineering and platform teams to deliver cutting-edge ML solutions and help shape the organisation’s data-driven future.

In Short

• Plan and manage the delivery and maintenance of machine learning/data science systems end to end.
• Manage, monitor and maintain the current machine learning systems across UNiDAYS.
• Identify, investigate and resolve technical issues within the data science/machine learning systems.
• Work effectively with platform teams to ensure machine learning infrastructure is set up correctly.
• Support the development of best practices around statistics, coding QA, project delivery.
• Deliver working MVP solutions to quickly prove hypotheses or new data products.
• Act as a coach and mentor to the wider Data & Insight team.
• Evaluate and measure your own performance and seek feedback for continuous improvement.
• Support R&D initiatives within the business.
• Communicate issues and resolutions to stakeholders and end users.

Requirements

• 5+ years experience as a data scientist/machine learning engineer.
• Extensive maths and computer skills, proficient in machine learning concepts.
• Proficient in using Python and SQL to production standards.
• Good understanding of software development principles.
• Experience with cloud services, ideally AWS.
• Experience with big data technology (ie. Redshift, Hadoop, Spark).
• Experience with data science/machine learning platforms such as Sagemaker is desirable.
• Experience working in multidisciplinary teams.
• Good general knowledge of building and maintaining machine learning systems.
• Experience in monitoring machine learning systems.

Benefits

• 25 days holiday per year increasing with length of service.
• Competitive salaries.
• 4pm finishes every Friday.
• Company bonus scheme.
• Private health insurance.
• Income protection policy.
• Life assurance policy.
• Support for home working for all new team members.
• Regular team building activities.
• Good Vibes Program for remote working experience.