Szymon D.
Senior Data Scientist @Plandek
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WORK HISTORY
Senior Data Scientist @Plandek
Manchester, GB
Designing, developing, and productionising the first range of fully scalable Infrastructure as Code GenAI products using Claude Sonnet, Vertex AI, Kubernetes, Elasticsearch, and Cloud Run, including:•• Dekka Chat: Developed an LLM-powered chatbot that serves as a personal Agile/analytics assistant, helping users navigate, interpret, and synthesise insights across Plandek’s GenAI analytics platform. Link to demo: Dekka Sprint Digests: Delivered personalised sprint reports on-demand via Slack and email, including C-level summaries, actionable insights, and detailed sprint assessments. •• Metric AI: Created a user-friendly tool for simplifying complex metric data visualisations across the Plandek platform, enabling broader understanding of analytical insights. • Developing internal best practice playbook for data science and experimental, agentic 16 step workflow for feature development, bug troubleshooting and spike research/protyping (including semi-automated API testing harness) to streamline processes and ensure rapid iteration with high-quality results.• Conducting internal seminars on cutting-edge data science methods (e.g, FAISS vector search), which were later implemented as part of the Config AI product by another team, enhancing the platform\'s capabilities.
EDUCATION
Lancaster University
Master's degree, Economics
ABOUT SZYMON D.
I am a Data Scientist and Machine Learning (ML) Engineer with over 11 years of experience leading high-impact projects across both government and commercial sectors. I have a proven track record of delivering complex, data-driven solutions, including Plandek’s GCP-based LLM products and Zuhlke’s GenAI services on the AWS Marketplace, focusing on MLOps and ensuring compliance with GDPR and the EU AI Act. At Azzuro Associates, I led the transformation of their data infrastructure, re-platforming legacy on-prem systems to a cloud-based Azure/Spark/Python/R/SQL ecosystem. This modernisation significantly reduced operational costs and enabled new capabilities, such as in-house ML for property valuation and horizontal Spark scaling for pricing microsimulations. Earlier in my career, I led large, cross-functional teams at the Department for Work and Pensions (DWP), where I coordinated with departments like HMRC and negotiated with key stakeholders, including the Office for Budget Responsibility (OBR). I successfully delivered high-profile projects, such as the Autumn Budget 2018 welfare forecasts and the Welfare Trends Report on Universal Credit, which played a key role in shaping government policy. This experience honed my leadership, collaboration, and decision-making skills.
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