Senior Data Science Manager - Finance Advanced Analytics & Reporting

We are searching for the best talent for Senior Data Science Manager - Finance Advanced Analytics & Reporting, As Senior Data Science Manager - Finance Advanced Analytics & Reporting (F/M/D) within the Global Finance Data Science team, you will lead the strategy, portfolio, and delivery of advanced analytics, financial and operational models, trusted reporting products, and governed data solutions that improve enterprise decision-making. You will provide functional leadership across multidisciplinary teams and combine deep Finance and ERP expertise with data science, business intelligence, and hands-on data engineering capabilities to turn complex business priorities into scalable, explainable, and executive-ready solutions.

The role will shape and execute the global Finance data and analytics roadmap; sponsor high-value use cases; establish standards for modeling, reporting, governance, and responsible AI; and ensure solutions deliver measurable business outcomes. The Senior Manager will partner with senior leaders across Finance, FP&A, Controllership, Data, Technology, Compliance, and regional teams to modernize planning and reporting, strengthen financial data products, reduce manual effort, and provide consistent visibility into performance, risks, trends, and opportunities worldwide.

You will be responsible for:

• Own and execute a global portfolio of Finance data science, advanced analytics, and reporting initiatives, aligning investments and sequencing with enterprise Finance strategy and measurable business value.
• Partner with senior Finance, FP&A, Controllership, Compliance, Data, and Technology leaders to frame strategic questions, define success measures, prioritize use cases, and secure sponsorship for adoption.
• Lead multidisciplinary teams and matrixed delivery partners through discovery, design, development, validation, deployment, and sustained product ownership; clarify roles, milestones, dependencies, risks, and decisions.
• Establish reusable standards for analytical methods, financial and semantic models, SAP data mappings, KPI definitions, documentation, testing, controls, and executive reporting across regions and business units.
• Provide oversight of SAP Finance data discovery across ECC, S/4HANA, CFIN, ACDOCA, SAP BW/4HANA, SAP Datasphere, and related platforms, ensuring source-to-target traceability, reconciliation, and fitness for purpose.
• Guide the application of forecasting, driver analysis, segmentation, anomaly detection, scenario modeling, machine learning, generative AI, and intelligent automation to high-value Finance decisions and processes.
• Sponsor rapid proofs of concept while setting clear hypotheses, scope, data requirements, acceptance criteria, decision gates, and value measures; determine whether to stop, iterate, scale, or transition solutions to production.
• Ensure production solutions meet enterprise expectations for architecture, security, privacy, responsible AI, data quality, lineage, auditability, reliability, performance, and cost management.
• Build trusted partnerships across global and regional teams, resolve competing priorities, manage executive-level risks and trade-offs, and communicate recommendations through concise, decision-oriented narratives and visualizations.
• Develop organizational capability by coaching data scientists and analytics professionals, fostering communities of practice, promoting knowledge reuse, and strengthening succession and talent pipelines.

• Demonstrated leadership of a global or enterprise analytics portfolio, including strategy development, prioritization, funding, governance, delivery oversight, adoption, and benefits realization.
• Deep expertise in advanced analytics and data science, including statistical analysis, forecasting, regression, time-series methods, anomaly detection, segmentation, scenario modeling, machine learning, and model evaluation.
• Hands-on fluency of SAP Finance data and reporting, including SAP ERP or S/4HANA, ACDOCA, CFIN, SAP BW/4HANA, SAP Datasphere, and SAP Analytics Cloud, including financial and planning data models.
• Prior experience with Python, SQL, PySpark, data preparation, feature engineering, exploratory analysis, visualization, and productionization, with the judgment to guide technical design and review team outputs.
• Experience leading solutions on modern analytics platforms such as Microsoft Fabric, Power BI, Databricks, SAP, Snowflake, Tableau, or comparable technologies, including dimensional, semantic, and self-service models.
• Ability to define enterprise KPI frameworks and executive-ready dashboards that translate complex financial and operational performance into clear decisions and actions.
• Expertise in data quality, source-to-target reconciliation, metadata, lineage, access controls, model governance, responsible AI, and audit-sensitive or SOX-controlled reporting environments.
• Knowledge of scalable architecture and engineering patterns, including medallion architectures, ETL/ELT, incremental processing, orchestration, testing, deployment, monitoring, reliability, and cost-performance optimization.
• Proven ability to influence senior stakeholders, lead through ambiguity and organizational complexity, manage external partners, and drive adoption across global, regional, and functional boundaries.
• Strong people and capability leadership, including coaching, mentoring, performance development, resource planning, and creation of inclusive, high-performing teams in direct or matrixed environments.

Required Minimum Education and Experience:

• At least 10 years of relevant experience in advanced analytics, data science, financial modeling, enterprise reporting, or data engineering, including substantial experience leading complex, cross-functional initiatives and analytics products from strategy through production adoption. Demonstrated success influencing senior leaders and delivering measurable outcomes in a global, matrixed organization.
• Bachelor’s degree in Computer Science, Data Science, Engineering, Information Technology, Industrial Engineering, Finance, or another quantitative discipline. An advanced degree in a relevant field is preferred.

Preferred:

• Deep SAP analytics experience in global Finance, FP&A, Controllership, or a regulated environment; implementation leadership across Microsoft Fabric, Power BI, Databricks, Snowflake, SAP Datasphere, or SAP Analytics Cloud; reporting modernization; SOX and audit readiness; and leadership of direct, matrixed, or partner teams across regions., Advanced Analytics, Budget Management, Compliance Management, Critical Thinking, Cross-Functional Collaboration, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Developing Others, Digital Fluency, Inclusive Leadership, Leadership, Strategic Thinking, Team Management

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