Patryk Hetnał

● Lead delivery of end-to-end GenAI and ML projects across retail, telco, and finance, acting as both technical lead and strategic advisor to executive stakeholders. ● Manage and develop a team of 6 consultants, building a high-performance culture grounded in ownership, mentorship, and outcome delivery. ● Define data science roadmaps aligned with client strategy — including CLV modeling, customer segmentation, and GenAI-driven campaign optimization. ● Drive project lifecycle from problem framing through model deployment, across GCP, AWS, Azure, and MS Fabric — combining business impact with robust engineering. ● Co-own pre-sales and growth of the Data & AI practice, contributing to 20+ successful engagements with sharp proposals, prototypes, and delivery strategy.

● Built and deployed real-time NLP models classifying IT support tickets, reducing manual triage and improving SLA compliance. ● Designed time-series forecasting models to predict incident volumes and optimize FTE planning, improving operational efficiency and budgeting. ● Created dashboards and diagnostics using Dash and Tableau, making model outputs accessible to non-technical stakeholders and driving data-informed decisions.

● Built predictive models estimating audit market size globally using Scikit-Learn and StatsModels, shaping strategic recommendations for senior leadership. ● Automated multi-step Excel-based workflows with VBA, significantly reducing analyst time and improving consistency of deliverables. ● Delivered executive-facing insights and dashboards using Power BI and Spotfire, enhancing visibility into competitive landscape across global markets.

- Ensuring that team valuations are prepared correctly and within deadlines - Analyzing and solving unusual cash and position breaks with brokers and clients - Automating excel-based processes by writing VBA macros

● Led daily NAV delivery for complex hedge fund portfolios, overseeing reconciliation processes and managing risk under strict deadlines. ● Coordinated with global stakeholders to resolve discrepancies, developing a reputation for precision and reliability in high-pressure environments.

● Supported operational risk reduction through process audits, exception handling, and coordination with global middle-office teams. ● Gained early exposure to large-scale data systems, audit workflows, and cross-functional coordination — foundations later built into data science practice.