Location: Manchester Airport, GB
MAG is the UK’s largest airport group. We own Manchester, Stansted and East Midlands Airports as well as MAG USA, a large Airport Services business based in Chicago. MAGO is our Digital Tech business; an airport-centric travel company, defining how airports increase their non-aero revenues. We create and deliver class leading e-commerce products and services to airport clients across the world using advanced MI, digital platforms and new and emerging technologies. We are an engine house of innovation and fresh thought, providing online customer solutions to our clients and improving the travel experience for us all.
Have a stroll around our office: https://youtu.be/0pYS_ghtWSU
Let us introduce ourselves and tell you why we’re a great place to work:
This Lead Data Scientist role is a key component of the expansion of MAGO’s Data Science capability as it seeks to expand its reach across digital touchpoints, focused around, customer journey, digital properties, and physical airports.
The Data Science team is critical to the growth of the business, developing our proprietary Data Management Platform, modelling and predicting customer, cohort and segment behaviours. As such, the Lead Data Scientist will join an existing team, where innovation is the norm.
As the Lead working within a small but capable team, you will be expected to bring provable commercial success, project design, and project management skills to help the Data Science team achieve their goals. Initially the role has two direct reports; one Data Scientist and one Data Engineer.
You will be engaged on critical development streams, covering many aspects of our digital priorities, such as e-commerce, reservations, distribution and digital marketing. As such, you will be directly involved in delivering machine learning solutions to problems of optimization, efficiency savings, and revenue enhancement. You will be organising and manipulating big data across many sources to shape the underlying information required to address complex problems.
As an experienced Senior Data Scientist, ideally with a Masters or Degree in a relevant field, coupled with experience in a commercial environment and demonstrable results in optimisation, efficiency savings, or revenue enhancement. We expect that you will have a strong analytical knowledge across a wide range of machine learning techniques, including: Regression, Decision Trees, Random Forests, Naïve Bayes, Support Vector Machines and knowledge of Deep Learning. You will have extensive commercial experience working with data through R and Python, from within an AWS environment. Furthermore, you will have experience with technologies such as Spark, Hadoop, Redshift, Elasticsearch, and MongoDB.
Further to technical skills, you will have strong and engaging communication skills that enable you to support your team colleagues to deliver projects, whilst engaging on a commercial level with stakeholders in the wider business.
What we Offer
MAG offers a very competitive base salary 11% pension, bonus, car allowance, parking and numerous other corporate benefits. This is a growing division, supported by one of the North West’s most iconic businesses. We can offer unparalleled career and development opportunities, along with the opportunity to make a genuine difference as we continue to grow.
MAG is a values led organisation and we are committed to providing equal opportunities in all areas of work and business. We want people to achieve their best, which will in turn positively impact on our customers and the communities in which we live and work. At MAG we empower people to be themselves within an inclusive and supportive environment, enabling everyone to achieve their full potential in line with their abilities and career aspirations.
As an inclusive employer, MAG wants to see every candidate performing at their best throughout the job application process, interview process and whilst at work. We therefore encourage you to inform us of any reasonable adjustments you might need to enable this to happen.
…please apply today.