Head of Customer Data Science
We have a very exciting opportunity for a Head of Customer Data Science in a highly agile, energetic, outcomes based environment. This role, reporting to the Director of Big Data, Analytics and Machine Learning and will help shape the data science capability throughout the group.
Making good use of machine learning and data science approaches, we aim to improve customer understanding, improve customer experience and build the richest data sets available in our market. We will do so by focusing on generating innovative products and services to deliver sustained competitive advantage for our brand.
The Head of Data Science role is an integral member of senior data and analytic team and you will be involved in hands on research and development of data driven solutions to real world problems. The work will encompass both improvements to existing products through innovative use of more advanced techniques as well as development of completely new offerings using Big Data tools.
You'll be part of a culture that encourages participation and discussion at all levels. You'll be able to see your impact in what we deliver day-to-day to our consumers.
At TUI, we never stop looking ahead, seeking new ways to delight our customers and grow our business. We recognise the power of digital and the massive contribution this brings to creating a truly unique and differentiated customer experience.
TUI Group is the world’s number one integrated tourism business. The Group umbrella consists of strong tour operators, 1,800 travel agencies and leading online portals, six airlines with more than 130 aircraft, over 300 hotels with 210,000 beds, twelve cruise liners and countless incoming agencies in all major holiday destinations around the globe. All this enables us to provide our 30 million customers with an unmatched holiday experience in 180 regions.
- Practical experience in relevant machine learning and data modelling techniques used in supervised problems such as decision trees, Random Forests, Gradient boosted machines, linear/logistic regression, deep learning, or unsupervised problems such as clustering and dimensionality reduction. All involving complex/high-dimensional data (e.g. image, text, video, speech, time series).
- The ability to work collaboratively and proactively in a fast-paced environment interacting with both a non-technical and technical audience.
- Interest in using ML to drive a meaningful impact to the consumer experience and business.
- Expertise in one or more programming/scripting languages (e.g. Python, R, Matlab)
- Good ability to interpret business requirements, translate into data science problems and deliver high value outputs.
- Ability to work quickly and iterate through trial-and-error, rather than spending an excessive amount of time designing the most robust methodology to deploy at the outset
- Ability to make data tell a story through data presentation / visualisation tools and techniques
- A real can-do attitude with a willingness to just get on with the job and make great things happen
- Research new data modelling, machine learning and data mining techniques for application across functions such as recommender systems, optimisation, pricing, time series forecasting, uplift evaluation and AB testing, Natural Language processing, computer vision, clustering and segmentation.
- Research and evaluate new datasets like clickstream, geo-location, market research, contextual, undertaking data discovery and exploration to identify opportunities to develop strategies and techniques to improve results.
- Leverage state-of-the-art big data tools (such as Spark, Python, R) and techniques to build innovative solutions using appropriate modelling techniques and data sets with a focus on implementation.
- A major part of this role will spear head recommendation and personalisation across the group.
- Develop and embed improvements to data science processes, in particular around building, deploying and monitoring.
- Explore different ways for data visualisation.
- Look creatively at our data challenges and map out the best approaches to tackle them using the state of art machine learning.
- Mentor other Data Scientists, Analysts and Data Engineers to implement statistical analyses and data/machine learning pipelines.
- Act as lead on cross team projects involving multiple stakeholders.
- Create prototypes for new/improved customer experience features and turn machine-learning outputs into operational data products.
- Assist in building a Data Science brand for TUI in the market using social media, conferences and events.
- Drive the implementation and scale-up of algorithms for bespoke customer experience.
- Set up and conduct large-scale experiments to test hypotheses and drive product development.