25 of 25 Use Case Jobs in South London

unifying diverse data sources across the organization. Data Modeling & Quality: Build and optimize robust data models specifically for complex querying and analytical use cases, and ensure data quality, integrity, and security across all systems. Reliability & Monitoring: Construct highly available, fault-tolerant systems for high-volume data ingestion ...

practices Experience working with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details ...

DMBOK, DCAM, and COBIT. Experience in large-scale financial institutions or treasury functions. Knowledge of data vault modelling and graph modelling for advanced use cases. Familiarity with data observability tools and practices to monitor data health, lineage, and reliability across pipelines ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

across the full lifecycle, from problem definition and experimentation through to deployment, governance and ongoing optimisation. What you'll be doing Leading the use of advanced analytics, machine learning and AI within the data team Collaborating with Product and Engineering on strategic AI-driven initiatives Identifying and developing … high-impact use cases for data science and ML Helping define ML lifecycle standards, documentation and governance Communicating insights and model outputs clearly to technical and non-technical stakeholders What we're looking for Essential experience Strong grounding in statistical modelling, experimentation and inference Advanced Python skills (NumPy ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

Aveni is redefining how financial institutions use AI. We build real, production-ready agentic systems that reshape how banks, advisers and financial services firms operate, replacing fragmented processes with intelligent, end-to-end workflows. We have been recognised as Fintech of the Year for two consecutive years … make sure the prospects and customers in your portfolio adopt and grow with Aveni Spearheading market expansion by entering new customer segments and use cases, collaborating cross-functionally to differentiate our offerings and sustain a competitive edge Becoming an AI expert – developing deep knowledge of AI applications ...