Data Science Capability

Tender description

Why the Work is Being Done As part of our Data Strategy The Financial Conduct Authority is increasing it's advanced analytics capability. The FCA is seeking to grow its Advanced analytics and data science capability to take on multiple projects across the organisation Problem to Be Solved Projects: - improve operational efficiency and process automation, - enhance understanding of firms and markets, - better risk identification (through exploitation of varied data sets and analytics techniques). Using: - aritifical intelligence, - text analysis techniques, - unsupervised machine learning and clustering techniques, - natural language processing tools, extracting & collating key information Outcomes: - Complete 3-4 Analytics projects - Build credibility & demonstrate value of analytics to FCA stakeholders (outputs & communication skills) - Integrate resources to work effectively as the FCA Analytics team under FCA performance management - Provide key technical skills including ability to upskill project resources Who Are the Users The Analytics Hub will lead the development of organisation-wide capability to support a more analytics-led regulatory approach. Data is at the heart of the FCA's approach to regulation. The Analytics Hub will support users from across the FCA, in a variety of different divisions. Early Market Engagement Work Already Done Existing Team The Analytics Hub is a relatively new team, it is comprised of a mixture of: - FCA Resource, - External Academics - Secondees, and - Third party suppliers. Current Phase Not applicable Work Location 25 The North Colonnade Canary Wharf London E14 5HS Working Arrangments The supplier will be expected to work onsite at our London offices Security Clearance Standard FCA Security checks and confidentiality agreement - short SLA Additional T&Cs Skills & Experience All project resource must have experience and/or Accredited training in R or Python All project resource must have experience and/or Accredited training in SQL All project resource must have experience and/or Accredited training in VBA All project resource must have experience and/or Accredited training in Graphing (e.g. Neo 4) All project resource must have experience and/or Accredited training in Visualisation, Spotfire or Tableau All project resource must have experience and/or Accredited training in working with large data sets All project resource must have experience and/or Accredited training in data science supervised methods (e.g. stepwise, forward stagewise, LASSO, random forest, support vector machine, bagging etc) All project resource must have experience and/or Accredited training in data science unsupervised methods (e.g. clustering techniques, k-nearest-neighbour) All project resource must have experience and/or Accredited training in communication skills All project resource must have experience and/or Accredited training in presentation skills The supplier must have experience in fully integrating data science consultants into an existing client team The supplier must provide ongoing training and development for all project resources which is re-active to specific project needs Nice to Haves No. of Suppliers to Evaluate 5 Proposal Criteria Technical skills and experience Value for money Team structure Cultural Fit Criteria The supplier should have proven experience integrating consultants into an existing team The supplier should have a strong record on staff diversity The FCA are looking for a consultancy who can supply staff with a positive attitude, independence and a desire to innovate and make a difference Payment Approach Capped time and materials Assessment Method Written proposal Case study Work history Reference Presentation Evaluation Weighting Technical competence 60% Cultural fit 10% Price 30% Questions from Suppliers Budget range circa £100,000 (incl vat) other 6 months