Role Description - We are expanding our new team for our banking clients. - You will be a business/data Analyst, part of an agile team focused on exciting transformation challenges around data. - You will work with some of the largest banks in the world, on projects that will transform the financial services industry. - You will modernize related processes and set-up, develop, and optimize state-of-the-art solutions and the corresponding data management all the way from business analysis to implementation. - Gradually you will take on more responsibility for your topics, as well as lead sub-projects and smaller project teams. Qualifications - A successfully completed university degree. - Fluent English (German is a big advantage). - Experience with working with data (data analysis, working with large datasets, data quality management, e.g. formulating rules and criteria to validate data, analyzing and resolving data quality events). - Business Analysis (as-is process and data analysis, writing requirements, data mapping). - Knowledge about the financial service industry, about banking products and about accounting is a big advantage. - You are a team player, have good analytical and conceptual skills as well as perseverance. Requirements - Screening Call – Introductory chat with our recruiter. - Technical Interviews (1-2 rounds, depending on the project) – Discuss your skills with our experienced Capco colleagues. - Feedback & Offer – Receive an offer to join our team! Benefits - Paid sick days. - 25 vacation days (regardless of age). - Monthly cafeteria allowance (1.285 CZK/month) or contribution to the 3rd pillar. - Fully paid meal vouchers. - Multisport card with employer contribution. - Smartphone with 1TB data + Laptop. - Well-being & Community Engagement – Join yoga lessons, mental health webinars, running challenges, sports activities, or participate in our volunteering days. - Competitive Compensation (adjusted based on experience) + annual bonus & benefits package. - Long-term career – Indefinite period contract with opportunities for career growth.

Role Description Collection of data as needed for decision making, strategy development, assessment of health care quality, practice management, and clinical research. - Query of clinical database for system-wide requests. - Display data, interpret results, and develop ongoing formats which meet user needs. - Provide statistical information as required by various affiliated study groups and Children's Hospitals and Clinics of Minnesota. Location: Remote - Must be MN or WI resident Qualifications - Four year degree in health-related field. - RRA or ART RHIA or RHIT credential. - Previous experience with coding, nomenclatures, case mix analysis, and database query tools preferred. - PC experience required. Requirements - Must be a resident of Minnesota or Wisconsin. Benefits - Medical, dental, and vision insurance. - Retirement benefits. - Other fringe benefits. - Positions that require night, weekend, or on-call work may be eligible for shift differentials or premium pay.

• The Data Operations Analyst provides day-to-day operational data and reporting support across LRG. • The role focuses on supporting existing reporting outputs, investigating data issues, and assisting with data testing during migrations and system changes. • This role is execution-focused and works within defined processes, standards, and priorities.

• Lead the technical analysis of five interconnected IHS data systems: RPMS (electronic health record), Clinical Reporting System (CRS), iCARE population management tool, NIRS/National Vaccine Coverage dashboard, and GPRA performance measures • Document what each system measures, its data sources and methodologies, reporting frequency and outputs, and limitations producing a definitive Systems Analysis Report • Trace end-to-end data lineage from patient-level RPMS records through CRS extraction to national aggregation, and reconcile differences in data definitions across systems • Assess data quality issues, reporting inconsistencies, and interpretation errors that undermine confidence in coverage data • Translate technical findings into plain-language content for user guidance, process maps, and training materials • Support development of report-interpretation instruction: how to read the numbers, spot coverage gaps, and monitor progress over time