Data Scientist

Q1 Technologies, Inc.; Isleworth; On-site; GBP 110,000 - 150,000; Full time

Job summary

Q1 Technologies, Inc. is seeking a senior AI/ML Lead to architect and deliver live sports AI solutions, blending Computer Vision, ML, Generative AI, and data science to generate metadata and detect key events in streams.

You will design experiments, own production ML pipelines with robust MLOps, and ensure low-latency cloud deployments for peak traffic. You will guide a team of data scientists, translate domain sports knowledge into actionable models, and champion responsible AI, transparency,

Qualifications

• Proven lead-level experience delivering sports insights or data-driven ML systems.
• Hands-on with event data, tracking data, or other high-volume sports datasets.
• Strong leadership and mentoring in a fast-changing environment.
• Experience with ML frameworks (PyTorch / TensorFlow) and production deployment.

Responsibilities

• Lead end-to-end development of AI solutions for sports metadata and event detection.
• Design experiments, run A/B testing, and build dashboards for metrics.
• Implement low-latency cloud AI systems for live content and data streams.
• Ensure responsible AI practices and transparent data usage.

Skills

Sports data engineering

Lead-level engineering

Mentoring

End-to-end delivery

Responsible and ethical AI

Multi-modal data

Tools

PyTorch

TensorFlow

Job description

• 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 bring

• Proven 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.
• 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.