Permanent
London

Data Scientist

We have a very exciting opportunity for a Data Science in a highly agile, energetic, outcomes based environment.  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 of companies.

You will be working within end to end teams to deliver complex analytics and world class big data solutions. The role will play a key part in helping the TUI use data more effectively to improve operational processes related to sales, marketing, customer service and customer experience.

Apart from that, it is the development of Big Data solutions - Work with the wider Data & Analytics team to develop revenue forecast models, customer segmentations, churn models, customer lifetime value and recommendation systems. You will play a part in testing the output through practical application, working with business teams to use the model output and measure the impact

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.

  • MSc or higher in Statistics, Mathematics, Machine Learning or other quantitative scientific discipline
  • Relevant industry experience in an advanced Analytics and Data Science role, with commercial exposure to modelling customers, sales/revenue forecasting, customer segmentation and digital marketing, etc
  • Experience of taking a project from manipulating raw data, through exploratory analysis and algorithmic development, to production and ongoing improvement
  • Demonstrate where previous work has led to tangible financial benefits
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Forests of Decision Trees, Online Learning etc
  • Excellent applied statistics skills, such as distributions, statistical testing, regression, etc
  • Extensive experience with common data science toolkits, such as DataRobot, R, Weka, NumPy, Spark ML. Excellence in at least one of these is highly desirable
  • Experience working with data pipelines and modelling in a production environment
  • Expert data visualisation knowledge
  • Experience of using Cloud based platforms and tools preferably AWS
  • Great communication skills, comfortable taking complex ideas and communicating them to different audiences.
  • Self-sufficient with the ability to work autonomously when needed
  • An entrepreneurial mindset who figures out how to improve business processes and finds opportunities to apply data science techniques to real problems
  • An expert in SQL and RDBMS concepts, including experience in working with large datasets
  • Good scripting and programming skills using languages like Python and R
  • Delivering best in class big data solutions that improve the performance of key business processes (e.g. revenue forecasting, segmentation)
  • Identifying key data sources required to solve the business and undertaking data collection, pre-processing and analysis
  • Presenting information using data visualization techniques
  • Evaluating the model performance
  • Partnering with key business stakeholder, to deliver core capabilities into the business, and ensuring adoption of the capabilities is embedded within the business.
  • Automate manual processes of model building
  • Use advanced methods to provide a greater depth of insight.
  • Prototype new ways to visualize and understand data relationships
  • Innovate and looking for new ways to solve business problems to drive ROI
  • Define robust measurement methodology to assess and track the value deliver through the capabilities deliver into the business