Closed tender

Data Science Support Provision for Data Services & Analytics (DSA)

Details

Published
18 June 2020
Submission
2 July 2020

Tender description

Why the Work is Being Done Data Services & Analytics (DSA) is a centralised service within Home Office Enterprise Services Digital Data and Technology (DDaT) Directorate which has been at the forefront of efforts to re-imagine the department’s relationship with data. It has led the way in professionalising our approach to the acquisition and analysis of data, promoting dynamic insight-led and evidence-based decision-making tools and techniques. The DSA Data Science provision is fundamental to the development of effective analytical data products and delivers on DSA’s vision to be at the leading edge of data analytics in Government. Problem to Be Solved The Data Science team is at the forefront of data analytics within the government. The Home Office is currently seeking a provider to support the completion of deliverables and on-going development of data products. The Home Office wish to engage a team to drive delivery and provide continued data science specialist support to the Data Science team, including transition of products into live service. Who Are the Users Users are typically business users from the Home Office family, who utilise DSA data products to triage, search and draw further insight from data. Occasionally users will be other Government bodies, from outside the Home Office family. Early Market Engagement None Work Already Done The data science provision has been running for over four years and has delivered several data products, including: • Triage product – Assess, prioritise and/or classify data for further processing. • Enrichment product – Bulk search over integrated data sets. • Search product – search over integrated data sets. • Insight product – Identify and visualise trends in data. • Enrichment – data and statistics aggregation and presentation. Some of the existing DSA services are currently running on physical infrastructure, but the Data Science team will be required to support transition of these services to a cloud infrastructure. Existing Team The existing team is composed of 30 Civil Servants, from Associate to Principal Data Scientist levels, supported by a small number of contract resource. The successful supplier will be responsible for providing data science specialists to develop, maintain and monitor Machine Learning models and Information Retrieval products. They should actively take opportunities to exploit native AWS data science services and help to set the direction for transforming the way data science products are delivered in the cloud. The Authority specifically seeks a provider with the flexibility and processes to quickly provide surge resource to meet shorter periods of high demand. Current Phase Beta Work Location Work will be normally be carried out from a Home Office location primarily in Croydon, South London. Following the COVID-19 government guidance, the team will be required to remote work in a safe environment, and attend meetings via digital channels such as Skype for Business. Once the current restrictions are lifted, occasional remote working may be permitted with agreement from the relevant Product Managers and in line with Home Office policy. Working Arrangments Likely to be a mixture of on-site and remote delivery depending on the individual project. Once restrictions are lifted, the supplier will be required to collaboratively work on-site (5 days per week to allow sufficient stakeholder engagement and support to be provided). Supplier costs must be inclusive of all expenses. Supplier is required to use MS Project Online to provide time sheet information to I&P Finance on a monthly basis. The new supplier will be required to report to the Head of Data Science (or delegated representative), work collaboratively with live services representatives and report progress to the DSA PMO. Security Clearance All proposed personnel must have SC level security clearance prior to starting work (with willingness to acquire resources with NPPV3 and DV clearance, as required). Any resource not in current possession of SC security clearance must be willing to undergo SC security clearance. Additional T&Cs The work will be progressed by several Statements of Work which may be based on fixed priced, T&M or Capped T&M as appropriate. The Home Office will use the standard DOS 4 contract. 1.Travel expenses are payable for journeys outside the M25 (for Greater London based SOWs) otherwise pre agreed changes in line with HO Travel policy (subsistence is not payable). 2. Professions rate caps will be applied to all standard roles to align with HO rate benchmarks as stated in the ‘Budget Range Section'. 3. Seasonal furloughs may be required. 4. Maximum sub-contractor margin caps will be applied. Skills & Experience Demonstrable experience of developing new machine learning models and information retrieval products. Demonstrable experience of maintenance and iterative improvement of existing models and information retrieval products Demonstrable experience of applying a wide range of data science techniques methods, such as supervised machine learning, unsupervised machine learning, text analytics, network analytics, geospatial analytics Demonstrable experience of developing analytical pipelines to process streaming data and provide near-real-time model results Demonstrable experience of delivering data science products using a variety of suitable technologies, such as Python, SQL, Docker, GitLab, CI-CD, AWS, Neo4j, Gremlin. Demonstrable experience of delivering data insight work (e.g. data exploration and production of reproducible research to share with customers Demonstrable experience of delivering data analysis / exploration tools (e.g. interactive notebooks / data visualisation dashboards) Demonstrable experience of managing machine learning products at all stages, from discovery to live service Demonstrable experience of using leading edge analytical techniques and tools Demonstrable experience of developing and deploying models and products in Cloud environment Demonstrable experience of collaborating with business analysts, user researchers and customer product owners to understand requirements and translate into tractable analytical problems Demonstrable experience of providing thought leadership for tackling data science problems. Nice to Haves Demonstrate knowledge of legal, ethical and regulatory requirements relating to machine learning in the public sector Provide evidence of experience in skills and knowledge transfer of cutting-edge data science tools and techniques Account management able to provide summaries and clarity over day to day activities for Programme Managers. Have demonstrable experience of working within a central government environment Demonstrable (and recent) experience of supporting teams to meet the government’s Service Standard. No. of Suppliers to Evaluate 4 Proposal Criteria Team members and experience Team Structure Mobilise team Flexible resources Approach and methodology Value for money Identification of risks and dependencies and approaches to manage them Cultural Fit Criteria Ability to function effectively and collaborate in a multi-supplier environment Working successfully in complex public sector organisations Approach to proactive issue management, problem resolution and improving ways of working Commitment to diversity, inclusion and tackling issues relating to bullying, harassment and discrimination Payment Approach Capped time and materials Assessment Method Work history Presentation Evaluation Weighting Technical competence 60% Cultural fit 5% Price 35% Questions from Suppliers No questions have been answered yet Budget range the authority anticipates the service charges will be based on benchmarked costs around levels of technical resources at sfia levels range of (3 and 5). professions rate caps will be applied to all standard roles to align with ho rate benchmarks e.g. sfia 4 is £650 with full benchmarking guidance to be provided at rfp stage. sfia 1, 2,6 and 7 levels are not required.

Timeline

  1. Completed: Tender published18 June 2020
    Current notice
  2. Completed: Submission date2 July 2020

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