James Watson Email & Phone Number

London, GB

London, England, United Kingdom

• Equinox project, FactSet FundamentalsLanguages & technologies: Python, FastAPI, VueJS, AWS, Redis, SQL, Attic (FactSet database abstraction API), FactSet.io (container and deployment tool).
• Optimised financial concept collection logic, reducing loading times from approx. 45s to 3s.
• Increased stability for document and table loading, helping achieve a 99.99% application uptime.
• Decoupled in-app validation and implemented Cerberus (internal validation tool).
• Elimination of > 140k data inaccuracies between metadata cache and database.
• Implemented over 75% backend API testing coverage.Financial Investment Group pipeline, FactSet Deep SectorLanguages & technologies: AWS, PostgreSQL, Python, C#, AngularJS, Protobuf, Attic, FactSet.io, FQL (FactSet.

London, England, United Kingdom

• Lead a fast-paced, agile team focussed primarily on developing tools to automate or assist with the testing of pricing changes.Technologies: Python, Snowflake & PostgreSQL, Jenkins.
• Automated batch tests for new pricing rules to replace manual testing. This halved testing time and allowed for a complete set of risks to be tested each time, rather than having them tailored to the current changes.
• API load performance testing following the implementation of new pricing models.
• Oversaw a large project to ensure automatic insurance renewals were compliant with recent legal requirements. Developed a pipeline to collect and validate data, testing against current pricing models and generate a.
• Automation of processes and tasks within financial modelling software to allow pricing team members to work more effectively and with higher confidence.
• Real-time, interactive data dashboard to allow for assessment of price changes post deployment.

Cambridge, United Kingdom

• Introduced machine learning to the business, training models to classify significant driving events
• New incident classification improved from approximate a 40% successful notification rate to 76%. Once deployed this information was reported to customers in real time. Develop processes and tools to monitor and analyse.
• Battery state detection algorithm allowed a client to have real time information across a fleet of electric vehicles.
• Categorised self-install device removal events to detect unauthorised removal. This work was presented to CTO and drove physical hardware redesign to improve physical security.
• Device activity, ensuring KPIs were being reached, and allowing for the early identification and resolution of any issues. Ad-hoc analysis and presentation
• Creation of clear and concise incident analysis and reconstruction reports for insurers and authorities, often to be presented as legal evidence.