David Hopes

Senior Machine Learning Scientist @Depop

London, GB
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Apr 2022 — Present

Senior Machine Learning Scientist @Depop

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London, GB

Working for the Trust and Safety team on- Implementation of tree and transformer based binary, multi-class and multi-label classifiers for detection of out of app transactions, used cosmetics, medical items, tech items- Designed and implemented ML pipelines using Databricks workflows to build transformer based models- Lead the Shared Tooling group, focusing on ML processes, improving reusability- Took responsibility for real time inference serving and reinvigorated support and further development of it- Implemented offline and online model evaluation tooling, essential for triggering the above pipelines based on metric thresholds.

EDUCATION

2017 — 2020

Queen Mary University of London

Bachelor of Science - BS

SKILLS

PowerpointMicrosoft ExcelAbleton LiveCadMyriadJiraDjLogic ProPower BiBusiness StrategyAdobe PhotoshopJavascriptTeamworkRisk ManagementOs XProcurementSurveyingPostgresqlInformation Security ManagementApple ApertureStructural AnalysisSalesforce.comCustomer ServiceReporting & AnalysisJavaResearchMatlabCommunicationSalesforce.com AdministrationTraktorIso 27001PowerpivotInformation SecurityOperations ManagementSageInternal AuditEnglishPythonRadioAdobe Lightroom

ABOUT DAVID HOPES

Data scientist with research interests in natural language processing and computational pragmatics, the role of context within dialogue.Programming/Scripting/Frameworks – Python, Spark, PySpark, Java, JavaScript, TypeScript, SQL, DAX, Bash, PowerShell, Django, Angular, Tools – Visual Studio, Power BI, Jupyter Notebooks, Jupyter Lab, GitHub, JIRA, Confluence, TFS, GitLab, ZeppelinPlatforms - Sagemaker, Databricks, MLFlow, Airflow, Jenkins, DataDog, Cloud Platforms – AWS, Azure, Office 365Soft Skills – Intellectually Curious, Achiever, Learner, Futurist, Focus, Ideation

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David Hopes — Senior Machine Learning Scientist at Depop in London, GB | Unifers