Strategic Surveillance delivery

Tender description

Why the Work is Being Done Our goal over the last 24 months has been to extend upon the systematic operations across the FSA to effectively identify food and feed risks. We need to identify direct impacts such as a microbiological risk through to crime, changes in consumer attitude to food to changes in business models, then to technical advancements in the production of food and how we all engage with it. We must be able to protect consumers now, and in the future, with the foresight to predict and take action in a timely manner. Problem to Be Solved To optimise use of data, mainly open data, to identify emerging food and feed risks before they become a public health concern. Who Are the Users As the competent authority in charge of regulating the food and feed sector, the FSA needs to be aware of risk affecting UK consumers, whether related to food and feed safety or to authenticity. Developing a predictive capability within the Agency will allows us, and others, to take action to mitigate those risks. Early Market Engagement Work Already Done Please see Document linked below for an explanation of previous work and additional information on requirement: https://drive.google.com/file/d/1Kkh4FDSC3vhJDQwPYkqQXSMN--XtxcOU/view?usp=sharing Existing Team The Supplier will be working with an in house team consisting of: 1 * Head of Data 3 * Data Scientists 1 * Fast Streamer (data analytics experience) 2 * Research Analysts (part-time) Current Phase Live Work Location Food Standards Agency, Floors 6 + 7, Clive House, 70 Petty France, Westminster, London, SW1H 9EX Working Arrangments You will be expected to work openly and collaboratively on digital channels (eg slack, MS Teams, Office365 etc). You will be expected to attend face-to-face key meetings at FSA offices, be involved in catch-up calls, organise and run user testing sessions, and present findings. We expect the successful supplier to provide upskilling to permanent staff to increase internal capability. Security Clearance All supplier team members will need to be cleared to Baseline Personnel Security Standard, and may be requested to sign a non-disclosure agreement (NDA) Additional T&Cs Skills & Experience Development of ML models and prototype dashboard for intuitive predictive insights Strong technical knowhow of various Machine Learning platforms, tools, and algorithms Following an agile way of working centred around specific ‘use cases’ and delivering Prototypes / Minimal Viable Products Experience of data cataloguing, utilising Github for version controlling and deployment of dashboards Experience of building machine learning models is multiple programming languages: Python, R, SQL Experience of using Microsoft Azure platform for developing end to end pipelines for running AI / ML models: data ingestion, processing, modelling, and visualisation Experience of visualising AI / ML based outputs using R Shiny and / or Power BI Experience of working in multiple Data Science Libraries such as TensorFlow, Pytorch, Keras, Pandas, SKLearnSpacy, beautifulsoup, Numpy etc. Knowledge of conducting detailed analysis of datasets available – ingesting, cleaning, analysing and modelling data as per business needs using best practices Liaising with different parts of the business and with external entities to support the forward pipeline of use cases and areas for further collaboration Capturing use case requirements, other technical documentation related to the use cases in a systematic format Development of the analytical roadmap, implementation plan for operationalisation of use cases Experience of delivering business value in similar context – making sure business requirements are understood, validated via positive challenge and delivering value Demonstrable deep knowledge and applied experience of the Government Data Ethics Framework in AI/ ML models Demonstrable approach to ensure reusability by design – ensuring solutions are formulated from reusable capabilities as well as ensuring new capabilities are reusable Nice to Haves Familiarity/understanding of food & feed related risk and how data science may be applied to related risk signals Experience of collaboration software such Jira, Confluence, Trello, Slack and Teams Experience organising hackathons / stakeholder workshops to agree business requirements and necessary solution approach Experience working with public sector organisations Experience of how to develop, code, test, correct and document programs as part of a multidisciplinary team No. of Suppliers to Evaluate 3 Proposal Criteria Demonstratable delivery of solutions providing insight and delivery of measurable outcomes using AI and predictive modelling, including machine learning, neural networks and deep learning with disparate api/linked open data sources. Deep knowledge and applied experience of the Data Ethics Framework and supporting guidance from The Alan Turing Institute for the responsible design and implementation of AI systems in public sector. Demonstratable experience working with and leveraging the benefits of Microsoft Azure services and open source packages for efficient and robust end-to-end solutions. Experience of end-to-end lifecycle from discovery to operationalising production grade services, ensuring quality assurance, adherence with relevant legislation, code of practice regulation and guidance related to use of AI/service design. Your approach to delivering business value – making sure business requirements are understood, validated via positive challenge and delivered against while understanding the value being generated (i.e. business intent) Evidence of innovative thinking - how you promote thinking outside the set of existing organisational constraints to arrive the most appropriate and efficient route to deliver desired outcomes Demonstratable approach to AI governance to ensure models and their delivery process can generate results which facilitate explainable AI by being reproducible, traceable and verifiable. How you will ensure a methodical and measurable approach to knowledge sharing to support our development of in-house skills and experience and mitigate supplier dependencies Demonstrable approach to ensure reusability by design – ensuring solutions are formulated from reusable capabilities as well as ensuring new capabilities are reusable Demonstrable approach to simplicity by design with a clear focus on producing and positively challenging solutions to be as simple as possible Demonstrable approach to identifying risks, dependencies and proposing mitigations throughout the lifecycle Proposed team structure, capabilities and experience Enough depth and breadth of capability across the supplier resource pool and ability to flex as needed Describe how your proposal will optimise costs and state any additional value-add your organisation will provide Value for money Cultural Fit Criteria Be transparent and collaborative when making decisions Experience of successful collaborative working as part of a multi-supplier agile delivery team, sharing knowledge and experience within the team Able to challenge the status quo and use persuasion skills to achieve business buy-in Take responsibility for their work and a no-blame culture and encourage people to learn from their mistakes Bring agile mindset and principles into a developing organisation Payment Approach Capped time and materials Assessment Method Case study Presentation Evaluation Weighting Technical competence 60% Cultural fit 15% Price 25% Questions from Suppliers No questions have been answered yet Budget range the total value of the proposed call-off agreement will not exceed £3m. work packages will be raised under this proposed call-off approach for each project. work packages will be on a capped time and material payment profile. the fsa will not guarantee any minimum value of work under the proposed call-off agreement.