Head of Data Science
Founders4Schools Cambridge, London, UK £75k – £90k Full Time Any
About Founders4Schools

Founders4Schools (F4S) builds smart connections between schools and the world of work. F4S is an EdTech charity dedicated to improving the ecosystem for scaleups by closing the skills gap. F4S works with enterprise advisors, school co-ordinators and head teachers in primary and secondary schools throughout England and Scotland to help their pupils aged 8 to 16 reach the milestone of at least four encounters with employers each year and to help their pupils aged 16-24 reach the milestone of 140 hours of work experience placements.

Job Description

Overall purpose of role

This role will play an integral part in shaping the personalised guidance that young people and educators receive by using in depth Analytics, Machine Learning and Artificial Intelligence.

As Head of Data Science, you will be responsible for leading the advanced data science capability, specifically driving the enhanced guidance for our stakeholders.

Key Responsibilities


  • As Head of Data Science, you will help provide insight into existing priorities and to surface opportunities to build data science-driven products.
  • Set the direction for data science and analytics for the team
  • Influence the architecture, delivery, and evolution of interrelated (big) data systems
  • Follow best-practice engineering standards, such as architectural design, unit testing and test-driven development
  • Give technical advice to the team and participate in scaling a resilient and service-orientated architecture

Develop and grow Data Science capability:

  • Identify technical and strategic direction for the capability to grow business and optimise risk
  • Deploy software algorithms to uncover patterns in large-scale data sets to identify opportunities that can inform the basis for the personalised guidance
  • Design, develop, evaluate and maintain new creative intelligence solutions, from prototyping to production, at scale
  • Collaborate with the rest of the business to integrate guidance into the rest of the software, from design to production
  • Build and maintain strong relationships with the team to develop an understanding of business strategy and objectives, identifying the implications to define the data modelling goals for designated project areas
  • Design, develop and establish relevant frameworks, models and business practices to drive the data-centric approach to understand current business problems and strategy, with the provision of input into solutions

Enhance internal assets:

  • Drive collaboration through identification of and partnership with third-party sources of information to extend and supplement existing data sets
  • Enhance data collection procedures to include information that is relevant for building analytics pipelines and systems
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Perform data mining using best practice and state-of-the-art methods in line with the latest data regulations

Data Engineering:

  • Build and optimise a data and computational infrastructure that can handle batch large-scale analytics, real-time streaming analytics and perform machine learning, training and prediction to serve young people and educators with international expansion on the horizon
  • Work with developers to ensure all required monitoring, exception handling and fault tolerance is in place to maximize the robustness of the architecture
  • Build fault-tolerant distributed machine learning workflows, starting from R&D all the way to production

Stakeholder Management and Leadership:

  • Ensure all data analytics and designs are communicated in a business related manner, ensuring a constant link between how data inputs and outputs affect business strategy and outcomes
  • Create and deliver business orientated insights as to where the problems/opportunities lie and how resources may best be allocated to engage

Risk and Control Objective:

  • Ensure that all activities and duties are carried out in full compliance with the latest regulatory requirements


Person Specification:

  • Industry experience in a Data Science role, managing systems from research to production.
  • Deep experience of data science techniques, including the pragmatic implementation of Machine Learning, Artificial Intelligence and multi-variant analysis techniques
  • Experience with common data processing languages and associated frameworks, for example Python, R, numpy, pandas, tensorflow or keras.
  • Experience of tools used to deploy your solutions, including 3rd party solutions such as Segment, AWS, Google Cloud and Heroku
  • Experience with Data warehouse solutions such as Snowflake, AWS Redshift or BigQuery.
  • An ability to collaborate with senior stakeholders
  • The ability to be a structured thinker, able to clarify and simplify complex ideas
  • Ready to join a team in a fast-growing, dynamic and challenging environment in a new role
  • Relentless in pursuing new innovations and self-improvement and bringing new ideas & solutions to the team
  • Ability to self-manage and prioritize workload
  • Full of energy and able to persevere through technical issues
  • A team player willing to learn / share solutions and best practices from your colleagues
  • Ideally a Master’s degree or PHD
  • Ideally experience managing production data systems

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