CAPCO POLANDTRINITY GAMECapco at Data & AI Warsaw Tech Summit 2026 Capco drives digital transformation across the financial industry. A global consulting firm focused on financial services, Capco partners with leading banks, fintechs, and financial institutions to design and deliver next-generation data platforms, AI solutions, and digital ecosystems. From data strategy and modern platforms to AI-powered decision systems and GenAI innovation, teams unlock measurable value from data. What defines Capco? A fast, flexible, and entrepreneurial environment. Quick decision-making, creative thinking, and real ownership enable people to push the boundaries of what technology can achieve. Capco stands for: • Trusted partnerships with banks, payments providers, and financial institutions • Delivery of modern data platforms and AI-powered systems • Innovation across cloud, data engineering, machine learning, and GenAI • A community of engineers, architects, and consultants solving complex challenges Meet Capco at the Data & AI Warsaw Tech Summit 🚀At this year’s Data & AI Warsaw Tech Summit, Capco will share how financial institutions can move from experimentation to production-grade AI and scalable data ecosystems. Our experts will explore how organizations can: • Build AI-native architectures on modern cloud platforms • Scale machine learning and generative AI solutions across enterprise environments • Transform fragmented data into high-value data products • Embed AI into real business workflows and decision-making systems Capco Speakers at Data & AI Warsaw Tech Summit 🚀Andrzej Worona & Laura Żusin-Kaczmarek Topic: From Data to Meaning: Educating AI in Banking with Ontologies: Lessons from FIBO and Conversational Banking Time: 11:50-12:10 CET Intro: Many AI solutions still fall short when it comes to understanding and reasoning about complex financial concepts. The real challenge is about how financial knowledge is represented and shared with machines. Why does AI still misunderstand basic banking terms despite having access to vast amounts of data? How can AI truly understand financial concepts? Using the Financial Industry Business Ontology (FIBO) as an example of structured domain knowledge, we will discuss how formal, machine-readable definitions can provide the contextual foundation AI needs. By analysing selected conversational banking scenarios and example solutions, we will invite participants to reflect together on what the right semantic layer for AI in banking should look like. Join us to discover why the next leap in AI for banking isn’t just about more data or better models, but about building a structured understanding of financial meaning. WELCOME TO TRINITY GAME

• Perform various analyses to understand data sources and generate business insights; • Develop statistical models using different techniques; • Continuously refine and improve developed statistical models; • Monitor the performance of production statistical models; • Act as a technical reference for other professionals in the team; • Support the technical development of new business requirements; • Lead research projects aimed at opening new avenues in data analysis; • Create high-impact Data Science projects; • Present model results to business stakeholders to highlight the importance of model deployment, communicate obtained insights, and translate model outputs into business terms.

• Own end-to-end solutions: translate ambiguous healthcare and operational problems into AI/ML models that deliver measurable impact by selecting methods, building data/models, deploying services, instrumenting observability, and real-world feedback loops • Partner with Product, Engineering, and Clinical leaders to embed data science into workflows like claims processing, utilization management, provider network optimization, risk adjustment, etc. • Deliver clinical intelligence features such as autonomous chart review, disease detection, compliance forecasting, and quality analytics • Build AI/NLP/LLM models for document understanding and information extraction, including OCR, NER, and vision models • Advance quality and payment integrity: create models and automated QA to reduce manual review, increase accuracy, and surface documentation anomalies and audit risk • Champion engineering excellence: internal libraries, reusable components, coding standards, code reviews, and clear documentation • Own the lifecycle: monitoring, drift detection, alerting, and post-deployment reviews.

Role Description VideoAmp, Inc. seeks a Senior Data Scientist to work in New York, NY. Job duties include: - Develop and implement machine learning algorithms to analyze large-scale datasets, uncovering insights and trends that drive strategic decision-making. - Support the design, development, and deployment of advanced statistical models to optimize advertising campaign measurement and improve planning and targeting accuracy. - Communicate complex analytical concepts and results to stakeholders in a clear and concise manner. - Ensure the integrity and accuracy of data through rigorous testing and validation of models. - Work closely with engineering teams to integrate models into production systems, ensuring scalability and reliability. Qualifications - Bachelor’s degree in Statistics, Mathematics, Computer Science, Data Science, or related field (or its equivalent) plus 5 years of experience. - 5 years of experience in data science, with a strong focus on statistical modeling and machine learning. - 5 years of experience in statistical techniques, including regression analysis, hypothesis testing, Bayesian methods, and time-series analysis. - 5 years of experience with strong analytical and problem-solving skills, with the ability to work with complex datasets and extract actionable insights. - 3 years of experience with programming languages such as Python and SQL. - 3 years of experience with general machine learning frameworks and libraries. Requirements - Telecommuting permitted. - 40 hours/week, $169,541 - $208,000 per year. - Must have authority to work permanently in the U.S. Company Description