• People Data Analysis: Utilizing data from internal and external resources and applying statistical methods to find patterns in data related to recruitment, attrition, engagement, organizational structure, pay practices and more. • Connect Data with Business Need and People Strategy: Partnering with People Business Partners, Centers of Excellence, and Business leadership, identify data trends and incorporate business context to make insightful connections between experience and data. • Strategic Advisor: Offer practical and informed recommendations to improve policy, workforce planning, talent development, retention, etc. to achieve business goals. • Reporting and Visualization: Collect and synthesize data into user-friendly dashboards to support data-driven decision-making.

• Develop, maintain and optimize data extraction, transformation and loading (ETL) processes; • Analyze, model and process large volumes of data; • Build queries, stored procedures and routines for integration and information provisioning; • Support Business Intelligence, Analytics and Data Science initiatives; • Ensure data quality, integrity and governance; • Identify and resolve issues related to performance and availability of data environments; • Produce studies, KPIs and analyses to support strategic decision-making; • Collaborate with business areas, data engineering and systems development teams.

Role Description The Senior Manager of Finance Analytics leads the development, execution, and governance of analytics and data capabilities that support financial planning, performance management, and strategic decision-making. This role is responsible for identifying and implementing architecture and tools to deliver financial insights, predictive analytics, and data-driven recommendations that enhance the organization’s financial performance. The ideal candidate brings a strong foundation in business financial analysis, paired with technical analytics expertise and proven leadership skills. - Own the finance analytics and data strategy to ensure alignment with corporate financial objectives; design and manage the creation of future-state architecture. - Lead requirements gathering, down-selection, implementation, and ongoing improvement of reporting and analytical tools, including artificial intelligence (AI) applications. - Oversee the design and delivery of dashboards, forecast models, and analytical tools used by Finance and business partners. - Translate complex financial and operational data into actionable insights for senior leadership. - Partner with FP&A, Accounting, Operations, and other cross-functional stakeholders to identify analytical needs and drive financial performance improvements. - Drive improvements in forecast accuracy, cost analysis, pricing analytics, capital planning, and long-term financial modeling. - Ensure data integrity, consistency, and governance within financial analytics processes. - Present analysis and recommendations to senior executives in a clear, concise manner. - Prioritize analytics initiatives based on business impact and resource capacity. Qualifications - A bachelor’s degree in finance, accounting, data analytics, or a related field; advanced degree preferred. - 7+ years of experience in financial analysis, FP&A, or finance-focused data analytics. - Demonstrated expertise in business financial analysis, including forecasting, budgeting, variance analysis, and financial modeling. - 3+ years of team leadership or management experience. - Proficiency in analytics and reporting tools (Power BI, Tableau), financial modeling tools, and SQL or Python for data manipulation. - Strong understanding of data modeling, financial KPI frameworks, and performance measurement. Preferred Qualifications - Experience in aviation, aerospace, defense, manufacturing, or a similar industry. - Strong familiarity with enterprise financial systems (SAP, Oracle, Hyperion, Anaplan, or similar). - Experience working with cloud data platforms (Azure, AWS, Snowflake). - Background in predictive analytics, scenario modeling, or advanced statistical methods. Skills and Abilities - Ability to communicate complex financial and analytical concepts to non-technical audiences. - Strong business acumen with a strategic approach to financial decision support. - Collaborative leadership style with a focus on team development and continuous improvement. - Ability to influence and partner effectively across all levels of the organization. - Strong project management skills with an ability to juggle multiple priorities. Travel/Physical Requirements - Less than 10% Benefits - Most locations offer a 9/80 schedule, providing every other Friday off. - Competitive compensation & 401(k) program to plan for your future. - Robust medical, dental, vision, & disability coverage with qualified wellness discounts. - Basic Life Insurance and Additional Life & AD&D Insurances are available. - Flexible Vacation & PTO. - Paid Parental Leave. - Generous Employee Referral Program. - Voluntary Benefits Available: Longer Term Care, Legal, Identity Theft, Pet Insurance, and more. - Voluntary Tricare Supplement available for military retirees.

• Use SQL and other analytical techniques to investigate business questions and anomalies across policy, premium, coverage, claims, and BDX data. • Analyze, reconcile, and validate BDX/bordereaux submissions and partner/carrier feeds, identifying gaps, mapping issues, and reporting impacts. • Work with business stakeholders to identify and align data initiatives with business goals to determine data analysis and reporting needs. • Partner with stakeholders to build recurring reports and dashboards using BI tools and fit-for-purpose datasets; use SQL to source and validate logic. • Lead root cause analysis to explain data variances or emerging business trends; communicate findings with clarity and urgency. • Collaborate with data engineers to understand pipeline logic, recommend field-level enhancements, and support fixes across BDX ingestion, mapping, and transformation. • Define data models and structures that align with business requirements, ensuring data is organized and accessible for analysis. • Establish data quality rules, validation checks, and cleaning procedures for insurance datasets, including BDX submissions. • Monitor and escalate data quality issues with recommendations for resolution. • Own and document key business metrics, calculations, and definitions for downstream consumers. • Mentor and support junior analysts with analytical logic, quality checks, and data storytelling. • Maintain and update metadata that describes the data assets, ensuring proper understanding and usage of the data. • Create process flows and documentation for data collection, transformation, and analysis workflows.