• Assess and optimize Google Analytics tracking, including events, tags, and data collection strategies. • Develop a technical roadmap to align Google Analytics with business objectives. • Implement tracking enhancements using Google Tag Manager (GTM) and Google Analytics to improve data accuracy. • Conduct thorough testing (unit and end-to-end) to ensure data integrity and tracking efficiency. • Document technical implementations and provide detailed guidelines for future analytics improvements. • Collaborate with cross-functional teams (Marketing, Product, Data Management) to ensure seamless data integration. • Support enterprise data ingestion, ensuring Google Analytics data is correctly processed into the data warehouse. • Provide reports and insights, translating raw data into actionable business recommendations. • Monitor performance metrics and ensure the tracking system aligns with business KPIs.

• You analyze large volumes of sensor, condition, and event data from the switch diagnostics system Artemis • You develop, validate, and improve analysis approaches for fault detection, anomaly detection, and condition assessment • You derive robust insights from measurement data and translate them into clear statements about the condition of switch components • You support the further development of data-driven prognostic models for predictive maintenance • You work closely with infrastructure specialists to technically contextualize measurement data, damage patterns, and detected anomalies • You assess the relevance of analysis results for operations, maintenance, and technical optimization • You develop an integrated understanding of physical system behavior, digital analysis, and operational value • You coordinate closely with software developers on data pipelines, data quality, visualizations, and system integration • You help transfer analytical methods robustly into existing digital applications • You prepare reports, dashboards, and decision templates for internal teams and customers • You work with sensor specialists to assess measurement quality, signal quality, and sensor configurations • You contribute to test scenarios and strategies for the system's further development • You support field tests and pilot projects, evaluate results, and help transition analytical insights into production applications.

• Be a catalyst to help the card business functions operate strategically using data • Drive evaluation of competing priorities across business functions and appropriate disposition solutions that are right-sized and scalable • Drive business growth by identifying new opportunities and hypothesis development using data across Credit Risk, Portfolio management, Fraud and marketing • Independently manage cross-functional relationships across Product, Engineering, Operations, Credit Risk, and executive leadership • Influence stakeholders through clear communication and data-driven recommendations • Develop A/B test designs to implement a robust test and learn strategy • Perform ad-hoc analysis ranging from open exploration data analysis to specific root cause analysis • Analyze Credit Card engagement and credit performance and identify levers and patterns that can increase card usage and utilization • Liaison with Data Engineering and Product to build sustainable and scalable data solutions to address business’ current and future needs • Own and manage BI reports becoming a focal point for business’ data and analytics needs • Leverage AI tools to accelerate analytical velocity and democratize data through self-service agents and tools

• Perform extensive SQL-based data transformations, integrating data from multiple internal and external sources (e.g., claims, media, CRM, EHR-derived datasets). • Define, validate, and govern metrics aligned to pharmaceutical business questions (e.g., brand performance, HCP engagement, patient journeys). • Apply statistical reasoning to analyze trends, identify drivers of performance, and ensure analytical rigor in insights and recommendations. • Maintain and iterate on analytical datasets and workflows as new data is ingested. • Conduct thorough exploratory data analysis (EDA) to uncover patterns, anomalies, and opportunities within complex healthcare datasets. • Interpret and translate analytical findings into clear business insights, tailored for stakeholders across marketing, analytics, strategy, and leadership teams. • Manually scrub, structure, and normalize data as needed to ensure data quality and analytical readiness, particularly for deep-dive analyses. • Prepare datasets to support advanced analytics, including exploratory and explanatory machine learning techniques, ensuring accuracy, consistency, and scalability. • Develop data visualizations and dashboards that clearly communicate insights and support decision-making. • Collaborate cross-functionally with data science, technology, media, strategy, and client-facing teams to align analyses with business needs. • Document methodologies, assumptions, and data limitations to support transparency and reproducibility.