• Partner with stakeholders to understand business needs and translate them into data, reporting, and analytics solutions • Design, develop, and deliver reports and dashboards to support operational performance, KPIs, and strategic decision-making • Analyze large and complex datasets to identify trends, insights, and opportunities for improvement • Create and maintain data models and reporting frameworks to enhance data quality and accessibility • Develop Tableau visualizations and dashboards to communicate insights in a clear and actionable way • Support ad hoc data requests, providing timely and accurate analysis to stakeholders • Identify and contribute to process improvements and system enhancements • Collaborate on cross-functional projects, supporting business initiatives and data-driven strategies • Ensure data integrity, accuracy, and consistency across systems and reports

• Lead the design of end-to-end analytics and business solutions that address complex challenges and align with organizational priorities • Conduct advanced requirements analysis, translating business needs into scalable, high-performing solutions • Partner with business and technical teams to design, validate, and implement solutions, ensuring alignment with strategy • Develop and deliver insightful reports and dashboards (e.g., Tableau) that drive data-informed decision-making • Define and standardize KPIs, metrics, and reporting frameworks to support operational and strategic goals • Ensure accuracy, usability, and alignment of analytics outputs with business objectives • Act as a trusted advisor to senior stakeholders, facilitating discussions and influencing key decisions • Lead and participate in workshops, strategic initiatives, and high-impact projects • Mentor and support junior analysts, promoting best practices in business analysis, data modelling, and reporting • Contribute to process improvement initiatives and strategic planning efforts • Define and document data requirements, mappings, and semantic models for analytics solutions • Collaborate with data teams to ensure data quality, integrity, and governance standards are upheld

Manage market data inventory and vendor contracts while collaborating with internal teams to optimize data infrastructure. Ensure compliance with reporting requirements and support procurement activities to enhance operational efficiency.

• Lead advanced data analytics, statistical modeling, and predictive analysis initiatives to support readiness based sparing models to support decision-making and strategic planning. • Partner with senior stakeholders to define analytical objectives, shape problem statements, and translate business challenges into actionable, data-driven strategies. • Enforce, maintain and contribute process improvements to documented enterprise data definitions, business rules, governance frameworks, and data quality standards. • Provide technical leadership and mentorship to junior analysts, supporting skill development and analytical best practices. • Serve as a trusted advisor and subject matter expert on data analytics methodologies, tools, and advanced analytical techniques. • Contribute technical expertise in data needed and structure to develop and model the simulation to identify the most effective option on the readiness cost curve. • Participate in planning sessions to acquire detailed information develop data pipeline architecture that align with project requirements. • Extract supporting data from identified tools, review available supportability reports and engineering details to assess quality of data prior to developing a readiness at cost model. • Document data gathering processes, pipeline configurations, and data flows to ensure consistency and future support. • Identify, define, and lead continuous improvement initiatives for analytics processes, data workflows, and system performance. • Ensure accuracy and completeness of all documentation. • Foster effective collaboration with cross-functional teams to achieve project objectives. • Communicate complex technical information clearly and effectively. • Utilize identified software and follow business rules and processes. • Identify areas to improve efficiency and accuracy and integrate those into modeling best practices.