*this role is open to remote working within the UK. Successful candidates will be required to travel to their closest UNiDAYS campus (London or Nottingham) on occasion.

The role in a nutshell

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.

Day to day responsibilities

• Plan and manage the delivery and maintenance of machine learning/data science systems end to end; this may be projects on your own or managing the delivery of others.
• Manage, monitor and maintain the current machine learning systems across UNiDAYS, ensuring that they still meet the requirements of the business.
• Manage, monitor and maintain machine learning operation databases and data stores.
• Identify, investigate and resolve technical issues which arise within the data science/machine learning systems.
• Communicate issues and resolutions to stakeholders and end users.
• Work effectively with the platform teams to ensure machine learning infrastructure is set up correctly and is fit for purpose. Identifying and supporting updates where required.
• Working with the end users and stakeholders to ensure systems still meet their needs and making the required changes.
• Support the development of best practices around statistics, coding QA, project delivery
• Work alongside Data, Product and Engineering to ensure data capture, architecture, analytical tooling is suitable for data science/machine learning systems.
• Support the development of automation activities within the team - enabling repeatable insight to be more readily available
• Produce and manage the technical requirements to product teams, data engineers and software engineers to translate data science/machine learning system MVPs into production
• Deliver working MVP solutions, to quickly prove hypotheses or new data products, to justify investment into production
• Support R&D initiatives within the business
• Act as a coach and mentor to the wider Data & Insight team in a technical capacity, developing their technical ability through collaborative work groups and training.
• Ambassador for the team
• You will evaluate and measure your own performance and seek feedback for continuous improvement. You also commit to regular check-ins with your line manager and to be proactive in completing your quarterly, Mid-Year and End of Year reviews to ensure your manager has enough time to complete before the deadline.

What we need from you

• 5+ years experience as a data scientist/machine learning engineer.
• Extensive maths and computer skills, with proficient in a range of machine learning (supervised and unsupervised), optimisation and advanced statistical concepts ie. Linear Algebra, Significance Testing, Regression and Natural Language Processing
• Proficient in using Python and SQL to production standards.
• Some experience of Shell scripting or appetite to learn is desirable
• Proficiency in other languages such as R, Julia are desirable but not essential.
• Good understanding of software development principles.
• Good knowledge of machine learning frameworks, like Tensorflow and scikit-learn
• Familiarity with data structures, data modeling, and software architecture.
• Able to carry out basic data engineering and database development.
• Good general knowledge of building and maintaining machine learning systems.
• Experience in monitoring machine learning systems, with the ability to identify areas for improvement.
• 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 but not essential.
• Experience with technically mentoring others
• Experience working in multidisciplinary teams, ie. Product Squads
• Nice to have: Experience and interest in martech platforms with built-in deployment capabilities

Who You Are

• High levels of curiosity - not taking the easy answer. Making sure that insight is thought out and looks at the problem from different angles
• Attention to detail - puts in mechanisms to check work and ensure things are accurate
• Strive for their output of their work to align to the strategy of the organisation and able to link their insight to value
• Team player - can work collaboratively on data science projects with other members of the team and the wider business
• Happy to get their hands dirty in all elements of the project - data cleansing, aggregation
• Good communication - both in terms of the presentation of work but providing updates to progress, setting clear scope with stakeholders, managing expectations
• Able to mentor, teach and guide other’s
• Able to manage the delivery of others within a wider project
• Care about the quality of output - aim for high quality outputs
• Keen to learn and share - new tools, coding, analytical approaches
• Respected for technical knowledge within the team
• Willing to take ownership of certain technical aspects / repeat delivery of the team (ie. automation)
• Ability to balance multiple projects in a fast-paced environment
• Excellent time management and organizational skills
• Proactive and self starter
• Comfortable dealing with ambiguity and rapid change
• Trusted member of the team across the business

What you can do

The behaviours that enable high performance

• Communication - Able to communicate outputs of data science/machine learning work in a clear way
• Be able to communicate issues and resolutions to stakeholders and end users in a clear and concise manner.
• Entrepreneurship / Innovation - Able to think creatively to build and implement machine learning systems. Coming up with solutions to problems when obstacles present themselves. Put forward ideas of new technology / tools / algorithms we can use.
• Stakeholder Management - Able to communicate with manager and stakeholder progress on work. Influence decision making based on the work you are doing.
• Leading Others - Find and take opportunities to demonstrate new tools, techniques to the team. Take an active role in supporting the development of others. Upholding and setting a good example for best practices, ways of working and governance.
• Prioritisation - Able to manage workload of themselves and others, within their projects, and communicate appropriately any challenges in a timely fashion.
• Collaboration - Able to work with others in the team and outside the team on solutions - removing some of the ‘black box’ nature of data science/machine learning, teams can input and we work on solutions together.

Academic Qualifications

Bachelor’s degree (or equivalent) in computer science, mathematics, physics or related field

Perks

We've accomplished a lot since we started in 2011, but in many ways, this is just the beginning. This is the chance for you to get in on ground zero. An opportunity to make a difference within the business with global reach. We are the world’s largest Student Affinity Network, with over 22 million verified members in 115 markets including the US, UK, Germany, India, Canada and Australia. We work with 800 of the world’s biggest brands globally, taking their products and services into the hearts and minds of tomorrow’s professionals, delivering engagement, building affinity and sales. You’ll also be working for a Great Place to Work CertifiedTM company who have been recognised on the UK’s Best WorkplacesTM for Wellbeing and UK's Best Workplaces for Women 2022 list. To find out more about our workplace initiatives, see our UK exclusive case study with Great Place to Work and be sure to visit our profile for more information.

We offer a fast paced, fun & social working environment where you can truly make an impact. We believe that work should enhance and complement your life which is why we leave it up to you to decide where you work. You can choose to work from your assigned campus (either Nottingham or London) or from home, whatever works best for your individual needs. Your manager may request you attend team meet ups at your campus but other than that it is up to you! We work hard at UNiDAYS , but we also believe in fair compensation for hard work. That's why we're pleased to offer all employees full access to our comprehensive benefits package.

Our perks include:

• 25 days holiday per year increasing with length of service, plus flexible bank holidays
• Competitive salaries
• 4pm finishes every Friday
• Company bonus scheme
• Company pension scheme
• Private health insurance (Vitality)
• Income protection policy
• Life assurance policy
• Employee Assistance Program
• Enhanced parental leave pay
• Core hours with flexibility around how/when you manage your time
• Regular team building activities
• The latest tech and hardware will be supplied from day one
• Good Vibes Program: we know we’ve all had to adapt to new ways of working and UNiDAYS has always taken pride in the community we’ve created in the office but we’re just as committed to creating an innovative approach to fostering connections and improving engagement outside of the office! We want to boost your remote working experience so think virtual parties, pottery classes, wellness classes and guest speakers just to name a few!
• Support for home working for all new team members. We will help assess your home set up and you can expense £150 towards any additional furniture you may need to be safe and comfortable when working from home

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status or disability status.