Global Knowledge Senior Data Analyst

Global Knowledge Data Senior Analyst

Global Knowledge Base | Enterprise Customer Experience

The Role

The Global Knowledge Data Senior Analyst plays a critical role in transforming Clarios’ Global Knowledge Base (GKB) from a traditional content and data repository into a globally connected, AI-enabled, and insight-driven enterprise capability.

Working closely with the Global Knowledge Sr. Manager, this role prepares, structures, analyzes, and translates customer, product, market, operational, and knowledge data into actionable insights that improve customer experience, support regional growth, and enable new business opportunities.

The Senior Analyst serves as a key bridge between data and business stakeholders across Customer Experience, Commercial, Marketing, Product, IT/Digital, and regional teams, helping turn complex information into scalable data products, decision-support tools, benchmarks, and business recommendations.

What You’ll Do (Impact Areas)

Data Analysis & Business Insights

• Collect, clean, validate, structure, and analyze data from multiple sources to ensure accuracy, usability, and analytical readiness.
• Analyze large and diverse datasets to identify trends, patterns, gaps, root causes, and business opportunities.
• Translate complex data into actionable insights, business implications, and clear recommendations for technical and non-technical audiences.
• Develop insight narratives and executive-ready summaries that support CX, commercial, product, and regional decision-making.

Reporting, Dashboards & Performance Analytics

• Develop dashboards, reports, and analytical summaries that provide visibility into knowledge utilization, customer behavior, market needs, and platform performance.
• Track KPIs related to knowledge management, data products, adoption, data quality, and insight effectiveness.
• Monitor performance and recommend opportunities to increase accuracy, relevance, usability, automation, and business impact.

Data Products & Value Creation

• Proactively identify opportunities to transform data and insights into scalable business solutions.
• Support the development of data products, decision-support tools, benchmarks, diagnostics, and insight solutions.
• Partner with business, Product, CX, Commercial, and regional teams to assess customer value, business value, feasibility, scalability, and monetization potential.
• Help convert knowledge and data assets into solutions that create measurable customer, commercial, and operational value.

Global Knowledge Base & Data Governance

• Support the consolidation, maintenance, enrichment, and expansion of Global Knowledge Base data.
• Help define and implement data standards, taxonomies, metadata structures, quality rules, and governance requirements.
• Monitor data quality and recommend improvements to data collection, modeling, and analytical processes.
• Strengthen consistency, accessibility, and usability of knowledge across regions and functions.

AI, Automation & Advanced Analytics

• Support the application of AI, automation, semantic search, content intelligence, recommendation logic, and predictive analytics across the Global Knowledge ecosystem.
• Assist with testing and validating AI-enabled knowledge solutions, analytical models, and automated insight capabilities.
• Identify opportunities to use emerging technologies to improve knowledge discovery, relevance, and customer decision support.
• Partner with technology teams to continuously enhance the effectiveness of AI-enabled capabilities.

Business & Technology Partnership

• Partner with IT/Digital and technology stakeholders to translate business needs into clear analytical, data, reporting, and platform requirements.
• Collaborate across CX, Commercial, Marketing, Product, and regional teams to understand business challenges and develop data-driven solutions.
• Communicate insights, opportunities, risks, and recommendations in a clear and business-oriented manner.
• Act as a translator between technical teams and business stakeholders to ensure alignment on requirements and outcomes.

Testing, Implementation & Continuous Improvement

• Support data publication, testing, validation, and business acceptance activities for data updates, dashboards, tools, and data products.
• Participate in System Integration Testing (SIT), User Acceptance Testing (UAT), and production readiness activities for Global Knowledge solutions.
• Monitor solution adoption, usability, performance, and data quality after implementation.
• Recommend and support continuous improvements that enhance speed, accuracy, scalability, and business value.

What Success Looks Like

• Global Knowledge data is accurate, structured, governed, and ready for analysis and AI-enabled use cases.
• Business stakeholders receive clear, actionable insights that improve decision-making.
• Dashboards and analytical solutions provide meaningful visibility into customer, product, market, and knowledge performance.
• Data opportunities are successfully translated into scalable tools, products, and decision-support solutions.
• AI-enabled capabilities improve knowledge discovery, relevance, usability, and productivity.
• Data quality and governance continuously improve across the Global Knowledge ecosystem.
• Strong partnerships are established between business and technology teams.
• Knowledge and data solutions demonstrate measurable impact on customer experience, operational effectiveness, and business growth.

Core Competencies

• Data analysis and analytical thinking.
• Business intelligence and data visualization.
• Data storytelling and executive communication.
• Business requirements gathering and translation.
• Problem-solving and root cause analysis.
• Data quality and governance.
• AI and digital technology awareness.
• Customer-centric thinking.
• Cross-functional collaboration.
• Stakeholder management and influence.
• Business and commercial acumen.
• Continuous improvement mindset.
• Project coordination and execution.
• Ability to navigate ambiguity and complexity.

What You Bring (Qualifications)

Required

• Bachelor’s degree preferred in Data Analytics, Business Analytics, Information Systems, Computer Science, Engineering, Digital Strategy, Business, or a related field.
• Minimum 5 years of professional experience in data analysis, business analysis, analytics, data management, digital platforms, or related functions.
• Experience collecting, cleaning, structuring, analyzing, and interpreting data from multiple sources.
• Experience translating business needs into technical, data, analytical, or reporting requirements.
• Experience working with both technical and business stakeholders in cross-functional, matrixed environments.
• Strong analytical and problem-solving skills with the ability to turn complex data into actionable business recommendations.
• Strong written and verbal communication skills, including the ability to communicate technical concepts and analytical findings to non-technical audiences.
• Ability to manage multiple priorities and projects within a fast-paced, global environment.
• Hands-on experience with one or more data and analytics technologies such as SQL Server, Snowflake, BigQuery, Redshift, MongoDB, Alteryx, KNIME, Hadoop/Hive, Oracle, Power BI, Tableau, Python, or similar tools.

Preferred

• Experience supporting data, analytics, Knowledge Management, Customer Experience, Business Intelligence, digital products, or related initiatives.
• Experience identifying business opportunities through data and translating them into dashboards, tools, product concepts, or decision-support solutions.
• Experience supporting small to medium-sized data projects from requirements gathering through implementation.
• Experience within Customer Experience, Commercial, Marketing, Product, or other customer-facing environments.
• Exposure to AI-enabled analytics, semantic search, recommendation engines, content intelligence, automation, or predictive analytics.
• Experience working with external technology partners, data providers, vendors, or analytics consultants.
• Ability to develop compelling executive presentations, insight narratives, and business recommendations.
• Interest or experience in data monetization, benchmarking solutions, diagnostics, customer decision tools, and scalable knowledge-based products.

Work Model & Travel

• Work Model: Hybrid, aligned with business and team requirements.
• Scope: Global, supporting stakeholders and regional teams across the organization.
• Travel: Occasional domestic or international travel may be required based on project and stakeholder needs.
• Key Partnerships: Global Knowledge, Customer Experience, Commercial, Marketing, Product, IT/Digital, and regional teams.

Our Commitment to You

• Opportunity to contribute to the transformation of a global, AI-enabled Knowledge Management capability.
• Exposure to strategic initiatives across Customer Experience, AI, analytics, digital transformation, and data products.
• Opportunities to develop expertise in emerging technologies, advanced analytics, and knowledge-driven business solutions.
• Collaboration with global, cross-functional teams and senior business stakeholders.
• A culture focused on innovation, continuous improvement, collaboration, and measurable business impact.
• Opportunities for professional growth while helping turn enterprise data and knowledge into capabilities that improve customer experience and create long-term business value.