Average Manager Scientist salary in London

Senior Data Scientist / Product Analyst II - Engineering PlatformLocation: London, UK (Hybrid) The MissionBehind every global streaming giant is a massive engine of internal tools and infrastructure. We are looking for a data expert to join our Platform Insights team. Your "customers" aren't the end listeners-they are the hundreds of world-class engineers building the applications used by millions. Your goal is to optimize the developer experience, ensuring our internal systems are fast, stable, and scalable.What You'll DoDrive Product Strategy: Partner with Product Managers and Engineers to define what "success" looks like for internal developer tools and cloud infrastructure.Full-Stack Analytics: Define key metrics, build robust datasets, and create high-impact dashboards (SQL/Python).Exploratory Research: Deep-dive into technical logs and user behavior to identify friction in the software development lifecycle.Influence Change: Communicate technical insights to senior stakeholders to prioritize high-value infrastructure investments.Who You AreThe Technical Analyst: You have 5+ years of experience in a quantitative role, with mastery of SQL and Python/R.Domain Enthusiast: You have a genuine interest in how software is built-familiarity with CI/CD, Cloud Infrastructure (GCP/AWS), or Software Architecture is a major plus.Bridge Builder: You can translate "complex system data" into clear, actionable business recommendations.Quantitative Background: Degree in Computer Science, Stats, Math, Economics, or a related field.Why This Role?This isn't a standard marketing analytics role. You will be at the heart of technical innovation, helping one of the world's most admired tech companies scale to a billion users by empowering the people who build it. Please apply here or share your updated CV to Randstad Technologies is acting as an Employment Business in relation to this vacancy.

£Up to £75,000 GBPRemote WORKINGType: Permanent Data ScientistOur client is a patented, award-winning cloud-based IoT technology provider, ranked 4th in the EnviroTech Top 50 and recognised globally for innovation in sustainable energy management and smart automation solutions. As a Data Scientist, you will play a key role at the intersection of smart building technology, IoT, energy optimisation, and predictive analytics. Working with rich telemetry data from connected assets, energy systems, and environmental inputs, you will design and deploy intelligent, scalable analytics that directly improve operational efficiency, reduce energy consumption, and enhance system reliability for global retail customers. This is a delivery-focused, innovation-driven role suited to a technically strong data professional who is passionate about sustainability software, AI, and transforming complex datasets into measurable business value. You'll have the opportunity to:• Perform statistical analysis and deep data interrogation across diverse, large-scale datasets • Develop, test, and deploy advanced analytics frameworks that uncover actionable insights • Design and implement end-to-end data science workflows from concept through to production • Translate R&D concepts and exploratory analysis into production-ready algorithms and reusable components • Build machine learning models and design experiments to optimise building performance and asset control strategies • Select and apply appropriate techniques including regression, classification, clustering, anomaly detection, and time-series analysis • Collaborate with internal teams to translate business needs into data-led solutions • Present complex technical insights clearly to both technical and non-technical stakeholders • Contribute to a culture of curiosity, continuous improvement, and innovation Your Responsibilities:• Analyse telemetry, energy, and environmental datasets to drive operational efficiencies and sustainability outcomes • Develop and evaluate machine learning models tailored to specific optimisation and energy use cases • Conduct exploratory research and develop prototypes or proof-of-concept solutions • Work closely with customer success and delivery teams to ensure analytics align with client needs • Deploy and validate models within production environments, ensuring robustness and scalability • Maintain and enhance internal best practices, documentation, and reusable frameworks • Stay informed on developments in Artificial Intelligence and Machine Learning • Communicate complex findings effectively to stakeholders across technical and commercial teams • Build strong cross-functional relationships to support successful solution delivery Key Requirements:• Degree in a quantitative discipline such as Applied Mathematics, Statistics, Computer Science, Engineering, or Physics • Proven experience working as a Data Scientist, ideally within client-facing software or optimisation-focused environments • Strong proficiency in Python or R, using libraries such as pandas, NumPy, scikit-learn, TensorFlow, or equivalent • Strong SQL skills for data extraction and analysis • Solid foundation in statistical techniques and machine learning, including regression, classification, clustering, time-series analysis, and pattern recognition • Passion for data interrogation with strong analytical thinking and the drive to uncover actionable insights • Excellent communication skills with the ability to translate complex data into clear business value • Ability to work independently, manage ambiguity, and prioritise effectively You will gain exposure with:• Large-scale IoT and smart building datasets within a cloud-based SaaS platform • Energy optimisation and automation solutions delivering measurable sustainability impact • Enterprise retail customers operating globally • Agile methodologies and cross-functional collaboration across product, engineering, and customer teams • Cloud-based data platforms and production-grade machine learning deployment • A vibrant, entrepreneurial culture centred around listening, empowering, innovating, and accomplishing Why Join?:• Work with a globally recognised, award-winning IoT platform transforming energy management for high street brands • Deliver AI-driven solutions that directly reduce environmental impact and operational cost • Collaborate with ambitious, multi-skilled teams across international offices • Contribute to cutting-edge sustainability software at scale • Be part of a selective, merit-based organisation committed to diversity and excellence Interested? Apply Now, or Reach Out To Aaron O'Neill | LinkedIn

What you’ll do:Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams.Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment.Integrate model-driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data.Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring.Design, architect, and operate low-latency, highly reliable cloud-based AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production-scale performance.What you'll bringProven extensive lead-level engineering experience delivering sports insights or sports data–driven ML systems, with clear ownership of technical direction, mentoring, and delivery.Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights.Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi-modal sports data (e.g., numerical, spatial, video, or metadata).Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch, TensorFlow), including taking models from experimentation into production model serving.End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure-as-code practices.Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day to day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary.Experience designing scalable, low-latency architectures, including real-time or near-real-time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases.Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders.