Role Description We are seeking a Senior Data Scientist to lead AI-driven initiatives delivering machine learning and Generative AI solutions within Capital Markets. This role focuses on building scalable models and applications for forecasting, anomaly/fraud detection, and LLM-based solutions (including RAG and agentic AI) on modern cloud platforms. - Design, develop, and deploy machine learning models for forecasting, classification, and anomaly/fraud detection - Architect and implement Generative AI solutions, including RAG pipelines, prompt engineering, embeddings, and vector databases - Build scalable AI applications leveraging LLM APIs, orchestration frameworks, and agent-based systems - Develop modular, production-ready Python applications following robust software engineering practices (SOLID principles) - Deploy, monitor, and optimise models using MLOps practices on platforms such as Azure, AWS, and Databricks - Analyse large, complex datasets to derive actionable business insights - Collaborate with cross-functional teams and effectively communicate outcomes to technical and business stakeholders Qualifications - Strong expertise in machine learning, statistical modelling, and data science techniques - Hands-on experience with Generative AI, including LLMs, RAG, prompt engineering, and vector databases - Practical experience with AI/LLM frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar - Solid understanding of anomaly detection techniques (e.g. Autoencoders, XGBoost, Isolation Forest) - Proficiency in Python and SQL, with ability to develop complex, modular, and maintainable applications - Strong understanding of software engineering principles, including SOLID design principles - Experience with Databricks and cloud platforms (Azure Preferred) - Good understanding of Capital Markets domain and fraud detection use cases Requirements - 6+ years of experience in Data Science, Machine Learning, or AI-related roles - Bachelor’s degree required. Attributes - Strong analytical thinking and problem-solving skills - Clear and effective communication with both technical and non-technical stakeholders - Delivery-focused with a pragmatic, cost-conscious mindset - Ability to work independently and collaboratively in cross-functional teams

• Build-up of a strong customer base leading to key accounts • Initiate and support all necessary actions to be included in the AVL of hyperscalers, such as NVIDIA, Google, Meta, AWS • Provide product Management & Engineering with necessary technical and commercial information to be able to specify and design a dedicated product portfolio or customized solution • Nurturing long-term customer relationships • Retaining existing business • Driving account growth through upselling, and coordinating with internal local and international teams to ensure smooth service delivery • Act as the face of the company, handling day-to-day communications and client inquiries • Welcome new clients, ensuring they understand the product or service and setting clear expectations • Schedule recurring meetings to review progress, gather feedback, and align on goals • Keep clients engaged and satisfied to minimize churn • Identify opportunities to offer additional products or services that solve client challenges and drive company revenue • Understand each client's specific business goals and tailor your company's offerings to help them succeed • Act quickly to resolve client disputes, address complaints, and assist with escalations • Anticipate risks and prevent bad surprises to ensure smooth business continuity • Work closely with product, sales, marketing, and technical teams to execute client projects and meet deadlines • Represent the client's needs internally, ensuring the buyer experience is prioritized while balancing the company's profitability • Oversee and assist with renewals and contract negotiations • Analyze account metrics, prepare progress reports, and present findings to both clients and internal stakeholders • Supports & Assists in monitoring ongoing global PTD Data Center key projects (inquiries, quotes, orders). • Supports Sales and Business Development in developing, implementing, and continuously optimizing the sales and marketing strategy. • Assuring order and demand forecasts & planning and provides necessary information to plan operations & production capacities, schedules and timing of necessary additional investments in equipment and/or resources • Supports Stäubli's internal departments in handling customer complaints. • Monitors the market and periodically reports on market developments, products, competitors, new trends, target achievement, and important events. • Supports new product launches. • Assists with controlling and reporting local sales activities, including revenue, growth, market, product, and customer-related targets for the sales and segment managers. • Supports the creation of sales budgets and forecasts.

• Develop AI and ML solutions to drive improved business performance and efficiency across domains • Lead end-to-end AI/ML projects from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring • Dissect and solve complex business problems using analytical and quantitative approaches to identify patterns and correlations in large complex data sets • Integrate and curate data from a wide range of internal and external sources to develop rich datasets for predictive & prescriptive modeling as well as machine learning • Define and implement best practices to generate accurate reports, visualizations & dashboards to explain results simply and succinctly to technical and non-technical users • Create models for visual recognition, processing of natural language that analyze complex data to make predictions or decisions, mimicking human intelligence • Identify the most effective model architecture and parameters to drive accuracy and performance • Liaise with stakeholders to understand their needs and concerns and develop concise analytics to provide actionable insights to influence strategy and performance • Build partnerships, share knowledge, and deliver valuable predictive insights to inform strategic decisions, while highlighting potential risks and opportunities

Role Description As part of the Data Intelligence team, the Data Scientist strengthens decision-making in alignment with World Vision Canada’s mission and impact. The role delivers advanced analytics that enable confident action, improve experiences, and support digital enablement and innovation. - Designs and delivers end-to-end analytics solutions, from data sourcing and preparation through to development. - Applies statistical and machine-learning techniques to solve complex business problems. - Partners with cross-functional and technical teams to support deployment and maintenance. - Communicates insights clearly to drive understanding, adoption, and action. - Contributes to scalable, integrated solutions in a digital environment. - Advances insights-led decision-making and supports the Data Intelligence mandate. - Integrates diverse datasets and translates analysis into actionable insights. Responsibilities - Leads the design and development of advanced analytics solutions (e.g., customer lifetime value, churn prediction, segmentation). - Defines analytical approaches to ambiguous problems by partnering with stakeholders. - Sources, integrates, and prepares complex datasets from internal and external systems. - Applies statistical, machine learning, and data mining techniques to identify trends and patterns. - Enables deployment and ongoing performance of analytics solutions. - Translates analytics outputs into actionable recommendations through storytelling and data visualization. - Supports adoption and effective use of insights by guiding stakeholders. - Strengthens data trust and accessibility by contributing to well-structured data assets. - Identifies and implements improvements to analytical methods and tools. Qualifications - Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field, or equivalent experience. - 3–5 years of experience in data science or advanced analytics, including relevant academic research. - Strong foundation in statistics and machine learning, with experience applying techniques such as regression, classification, clustering, forecasting, and experimentation. - Strong Python or R (e.g. pandas, NumPy, scikit-learn) and SQL for working with large, complex datasets. - Experience working with modern data platforms (e.g. Azure, Snowflake). - Expertise in Natural Language Processing and applying domain knowledge to extract insights from unstructured data. - Experience designing and delivering end-to-end analytics solutions. - Ability to translate ambiguous business problems into analytical approaches and actionable insights. - Strong communication skills, with the ability to explain complex analysis clearly. - Certification in machine learning or big data and experience working in Agile environments considered assets. Benefits - Health Spending Account. - Up to 6% matched pension contributions. - Parental leave top-up. - Generous paid vacation, sick days, wellness and personal days. - Office closed extra days before long weekends (6x/year).