Lead Product Owner

Our Atlanta based Fortune 500 client is seeking a Lead Product Owner to oversee the development and management of data science and analytics products. The ideal candidate will work closely with cross-functional teams to align data initiatives with business objectives, define roadmaps, and prioritize tasks to ensure seamless data workflows.This is an Atlanta-based, contract-to-hire position, requiring a hybrid work setting with a few days per week in the office. Job Responsibilities Stakeholder Collaboration: Maintains ongoing communication with stakeholders, defining priorities, managing expectations, and negotiating in complex situations. Builds trust and ensures key stakeholders are involved in decision-making. Translates data-driven insights into accessible and actionable strategies for end users. Identifies and addresses gaps in data strategy with strong problem-solving and critical thinking skills. Balances technical constraints with business objectives to drive value. Product Owner: Partners with the Product Manager to align Data Science and Analytics priorities with business goals. Collaborates across Data Solutions, Intelligent Automation, and AI teams to leverage full IADA capabilities. Owns backlog management, prioritization, and acceptance criteria, ensuring meaningful value-driven metrics. Frames problems, opportunities, and user needs to facilitate discussions and generate innovative solutions. Leads and participates in Agile ceremonies, ensuring alignment with best practices. Defines and communicates product strategy, linking team efforts to organizational goals. Prioritizes business impact over a technology-first approach when evaluating alternatives. Collaborates with engineers, analysts, data scientists, QA and business teams to ensure smooth delivery. Engages in continuous learning and fosters a Product Community of Practice, including mentoring and coaching. Capability to convert technical outputs into meaningful business insights that drive decision-making. Ensuring data team initiatives align with sprint objectives and deliver measurable business value. Proven ability to craft clear, concise user stories and prioritize them based on their business impact. Expertise in utilizing feedback loops to continuously enhance and optimize data products. Technical: Strong understanding of Analytics and Data Science workflows. Understanding of Machine Learning (ML) lifecycle and model deployment. Experience with data visualization tools (Power BI, Tableau). Familiarity with cloud platforms (Azure, AWS) and technology integrations. Works with technical leadership to address challenges and solutions. Stays updated on emerging data technologies to enhance product capabilities. Agile Team Experience Fosters a positive team culture, ensuring engagement, learning, and collaboration. Encourages open communication and creates a safe environment for innovation and growth.