• Responsible for the development and maintenance of program dashboard in PowerBI • Provide financial data analytics for the program by leveraging prior knowledge of AI/ML, Python programming, and data modeling • Program life-cycle activities such as project setup/ maintenance, invoicing support, accruals, financial projections, subcontractor tracking, and month end close • Manage and administer a custom Sentinel Earned Value Lite Tool called, “PMX” • Development and maintenance of Estimates at Completion (EAC)s • Responsible for a set of TDPs (Technical Direction Plans) within the PMX system, which includes TDP statusing, TDP EACs and forecasting • Significant interaction with the Program Managers, and may involve interaction with Ops/Line Management, Finance personnel, Contracts personnel, Procurement, senior technical personnel, and various other functional or support organizations • Implement business process reengineering improvements within the Sentinel Finance Team aiding in aspects such as invoicing and various other areas

Role Description Understand the Process Mining solution offered by Celonis and its existing capabilities. - Capable of building KPIs to highlight the use-case specific to processes and client requirement. - Hands on experience on building Analysis dashboard & Execution App. - Hands on experience in different components of Celonis like - Views, Action Flows, Skills, Knowledge Model, simulation and data explorer. - Capable of identifying and building Execution Gap use cases. - Should have good analytical skills. Qualifications - Should understand and implement client requirements. - Strong presentation and communication skills. - Should be able to create custom connectors. - Should know how to make API Calls. - Should be able to establish an end-to-end live connectivity – on premise as well as cloud and custom connectors. - Should be able to write complex SQL & PQL queries. - Should be able to implement Multi Event Log in custom projects. - Good to have knowledge about OCPM. Benefits - Flexible work arrangements to provide support, including remote work and flexible work hours. - Career growth programs and diverse professions to explore a world of opportunities. - Valuable certifications in the latest technologies such as Generative AI.

• Leverage complex datasets to generate actionable insights that influence payments & fraud strategy and drive business outcomes. • Support development and testing of payment and fraud rules: help define objectives, use data to inform and optimize rules, analyze A/B tests, and measure impact on key metrics. • Design, build, and maintain dashboards and reporting solutions to enable self-service analytics across the organization. • Collaborate with product, engineering, marketing, finance, and other teams to scope analytical projects and deliver insights. • Investigate anomalies and support root cause analysis for payment & fraud incidents. • Communicate complex findings clearly and effectively through presentations, reports, and data storytelling tailored to various audiences. • Advocate for data quality, governance, and best practices to ensure consistency, reliability, and security of data assets. • Mentor junior analysts and interns and contribute to the growth of the broader analytics community within the organization. • Participate in weekly payments syncs, sprint planning, and cross-team channels to stay aligned on priorities and incident response. • Independently identify high-impact business problems and develop the right data-driven solutions.

• Collaborate with engineers, logisticians and product managers to understand requirements, gather supporting information specifications and develop readiness based sparing model. • 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. • 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