Data Scientist

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Role: Data Scientist

Start Date: ASAP

Location: Osterley, West London

Duration: 3-6 months

Fancy working with the Europe's leading Entertainment Company? We are looking for a Data Scientist to join our team in West London.

The client is a large entertainment organisation; they excite and inspire customers with leading innovations and technologies in the entertainment industry. They strive to be the best for customers and the people working for them. They are always looking for ways to improve. That spirit has made us what we are today, and it will drive us to become what we want to be tomorrow.

We have a number of amazing opportunities for data scientists to join a transformation in how we use our data to improve our customers' experiences. We are investing significantly in building up a cutting edge internal team, focused on using data to enhance every part of a customer's interactions with us. We have made great progress in the last two years delivering >£100m p.a. of value through improving our data and our capability and are now expanding our data science team to take our intelligence to the next level.

To achieve this, we're looking for people with exemplary data science skills across the whole development pipeline from big data engineering to advanced model building to putting into production. In addition, you'll need to be commercially savvy, have a strong focus on practical & pragmatic use of data and a passion for connecting your work directly to the customer experience, making a real and tangible impact

Job DescriptionResponsible for developing and driving actionable customer intelligence from our core data assets using advanced analytics.Develop advanced analytics algorithms exploiting our rich data assets including viewing behaviours and content engagement on multiple platforms (linear, on demand, streaming etc), online engagement with digital (apps, website), customer service interactions, service quality and performance information and customer metricsEngage with key stakeholders (marketing, retention, service, finance) to understand business objectives and support these objectives through best use of advanced analytics approaches. Responsible for identifying the best analytical techniques, developing the solution, creating a framework for testing the solution, deploying champion challenger tests and measuring the incremental value to the business from the solution.Engage with our technology teams and data engineers to build compliant, efficient and scalable solutions for managing customer treatments.Strengthen our internal data science capabilities by continuously innovating and driving new ideas, building technology partnerships with our vendors, training and developing our people and creating a world class data science team.

RequirementsExperience building and deploying advanced analytics solutions in a large scale (preferably B2C) cloud environment.Expertise in at least 2 areas including Forecasting, Predictive Modelling, Optimisation, Clustering or NLP.Experience in deploying commercially viable applications using deep learning techniques combining structured and unstructured data is highly desirableAbility to quickly understand a business objective, problem solving to create an analytical solution and stakeholder communication are essentialCommercial knowledge and applications of data science to drive commercial value is a must - everything we do drives value into the business.Experience in data engineering, data modelling for advanced analytics, data processing on cloud, model management and app deployment on cloud is highly desirable.

SkillsEssential - Python with experience on GCP (BigQuery, GCS, Datalab, Dataproc, Cloud ML, Tensorflow)Good to have - SQL, SAS, R, Matlab, Keras, Torch, Caffe, Lua.Good to have - Spark, C/C++, Java

Analysis:Machine learning (essential) - Supervised/unsupervised learning, regression, decision trees, random forests, boosting, SVM, clusteringNeural networks (very helpful) - CNN, RCNN, LSTM, AutoencoderStatistical modelling (doesn't hurt) - GLM, Bayesian hierarchical models

Please submit CVs in the first instance