UK SBS IT18162 UKRI STFC Machine Learning & Data Science Architect

Tender description

Who Speclialist Work With The team is new and forming. There is a group leader (Prof Tony Hey) and potentially a senior data scientist will be on board by the time the specialist commences works. Two more group members start in October while the specialist will be working with the owners of the datasets from the national science facilities and at universities. What Specialists Work On To set up a Science & Machine Learning group area in the Scientific Computing Cloud and the Azure Cloud, with a range of different datasets for the different types of experiments at Rutherford Appleton Laboratory. The objective is to make a range of Machine Learning L toolkits – Microsoft’s Machine Learning suite, ScikitLearn, TensorFlow etc. – available and record the results of the different methods on different datasets and Cloud hardware in a set of files. Setting up these benchmark datasets together with some specimen results will be the major part of the work. Where the Work Takes Place STFC Rutherford Appleton Laboratory, Harwell Campus, Didcot, OX11 0QX Early Market Engagement N/A Working Arrangements The specialist will be based in the office five days a week and will be working with other colleagues by meeting, telephone, video conference and email where necessary. Standard hours are 9am until 5:30pm with an hour lunch break although there is flexibility. Travel will be seldom. Occasional remote working when necessary. Work Location STFC Rutherford Appleton Laboratory, Harwell Campus, Didcot, OX11 0QX Security Clearance Baseline Personnel Security Standard (BPSS) and Disclosure Scotland Additional T&Cs T&S as per UKRI policy. Skills & Experience Demonstrate how you will apply your skills and expertise: In data science and machine learning and how this will ensure the successful delivery of this project – 15 points To manage, structure, and analyse data, including building statistical models and using machine learning technologies and how this will ensure the successful delivery of this project – 15 points To utilise machine learning toolsets such as SciKit Learn, TensorFlow, etc. and how this will ensure the successful delivery of this project – 15 points To manage and organise the parameters and results of computational experiments and how this will ensure the successful delivery of this project – 15 points Nice to Haves No. of Specialists to Evaluate 3 Cultural Fit Criteria Demonstrate how you will work with other people throughout this project – 5 points Demonstrate how you will solve problems throughout this project – 5 points Demonstrate how you will share knowledge and expertise throughout this project – 5 points Assessment Method Evaluation Weighting Technical competence 60% Cultural fit 15% Price 25% Questions from Suppliers No questions have been answered yet Budget range up to £500 a day. the total value of this contract shall not exceed £69,500.00 (excl vat) including any options to extend.