Data Scientist

Sagacity
London
1 month ago
Create job alert

Purpose of the role


To support the design, prototype and delivery of innovative, data-led products by combining market insight, advanced analytics and modern data platforms. Working in closely with Product Managers and Data Analysts, this role will convert data assets and models into scalable, commercially viable analytical insights, data visualisations and product features.


The Product Innovation Analyst bridges commercial opportunity and technical feasibility, ensuring new products are designed with platform capabilities, data quality, performance and scalability in mind.


Principal responsibilities


  • Identify and define new data product opportunities enabled by advanced analytics, machine learning and large-scale data processing
  • Evaluate and test emerging AI technologies and analytical techniques and their suitability for use within our Customer Intelligence Platform to unlock new product capabilities
  • Drive product innovation from concept to launch, translating business and customer needs into technical product requirements and delivery specifications
  • Lead rapid prototyping and proof-of-concept development using Databricks notebooks, analytical outputs and machine learning techniques to validate product concepts
  • Own technical product definition, including data structures, feature sets, scoring methodologies, model architectures and delivery formats in collaboration with the Product Team
  • Define and monitor technical success metrics (data coverage, refresh latency, model stability) alongside commercial KPIs to optimise product performance


Product Innovation & Technical Design responsibilities:


  • Identify new product opportunities enabled by advanced analytics, machine learning and large-scale data processing
  • Identify new usage of existing attributes and products to create more value in existing data
  • Translate business and customer needs into technical product requirements
  • Support rapid prototyping and proof-of-concept development using Databricks notebooks and analytics outputs
  • Define product-level data structures, feature sets, scoring outputs and delivery formats in collaboration with the Product Team

Product Launch & Performance responsibilities:


  • Define technical success metrics (data coverage, refresh latency, model stability) alongside commercial KPIs
  • Support internal enablement by translating technical product detail into usable sales and client-facing materials
  • Drive continuous optimisation using usage analytics, customer feedback and platform performance insights


What success looks like in the role


  • Clear, concise and insightful data analytics which enable sound business decisions based on fact
  • Ability to translate data analysis into targeted information which can be converted into actionable improvements, based on specific client, sector, internal product need
  • Cross functional collaboration to enable continued improvement of Sagacity's Product Suite through the delivery of robust data insights
  • Ability to take accountability and ownership for client and internal deliverables
  • Your efforts result in streamlined data analysis, product builds and reduced time to market


Competencies and Behaviours


  • 1 -3 years analytics / data science experience
  • Practical knowledge of; Delta Lake architecture and versioned datasets, Data pipelines, orchestration and scheduling concepts
  • Proficiency in analytical programming language such as python and/or SQL, with the ability to interrogate datasets and validate analytical outputs
  • Experience designing data products using large-scale transactional, behavioural or marketing datasets
  • Understanding of data modelling concepts (fact/dimension models, feature engineering, aggregations)
  • Can balance time across multiple projects. Plans ahead working backwards from deadlines with all necessary steps e.g. testing, QA. Proactively identifies risk and suggests mitigation
  • Is curious, sceptical, inquisitive, suggests 'next steps' analysis and translates analytical findings to actionable insight
  • Flexible, self-motivated, good under pressure, has a commitment to personal development
  • Excellent communication skills, both written and verbal, with a willingness to engage and influence others
  • Commercial experience within Telecoms, Banking or Utilities industries; or within a data related consultancy company would be beneficial
  • Able to travel throughout the UK
  • Can be based at our London Office (min 2 days per week on site)
  • Have the right to work in the UK

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.