Demand and Design Accountability Define the product/data roadmap and capture comprehensive requirements. Design the solution with technical teams and capture the nuances to ensure E2E optimization and efficiency. Author technical data requirements and documents required throughout the delivery life cycle. Delivery Accountability Manage delivery against key technical delivery milestones. Ensure the technical teams are clear on the “why” from the perspective of the Business customer. Work with technical teams (Data Science, Data Engineering, Stewardship, Governance, BI/Visualization) to write and steward user stories and requirements in Azure DevOps. Ensure these teams are spending optimal time at work in their specialties. Manage the output and development of other Data Product Managers Manage business customer expectations and seek to eliminate disconnect. Collaboratively manage reporting that measures D&Ai execution against key programs. Go to Market and Adoption Ensure data, analytics and Ai outputs meet requirements. Translate the analytics solutions back to the business to ensure they are actionable, and business can drive value from those insights. Collaborate with business & transformation teams to embed analytics solutions and overcome implementation difficulties. Effectively manage key stakeholders at all levels within the organization. Foster collaborative team culture within PODs Compensation and Benefits: The expected compensation range for this position is between $118,700 - $198,800. Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process. Bonus based on performance and eligibility target payout is 15% of annual salary paid out annually. Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement. In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan.
Bachelor’s degree. 8+ years of Data Product Management in business facing functions which includes strong expertise in agile and product lifecycle discipline. 5+ years of experience leading/building advanced analytics and big data solutions or building enterprise SaaS. Deep understanding of fundamental machine-learning principles (for instance, training versus predicting, performance measurement, and overfit), as well as techniques such as random forests or neural networks. Familiarity with machine-learning technologies and tools, such as big data stack, Python, and visualization techniques. Knowledge of data architecture, modeling, and engineering concepts. Familiarity with Azure tech stack a huge plus. Familiarity with principles and tools for data governance and stewardship. Persuasive communication skills and an ability to break down complex information into relevant and digestible points for both technical teams and the business. Demonstrated ability to drive business-oriented and innovative solutions using data science, feature engineering and machine learning. Highly initiative taking with ability to identify and pursue growth and opportunities. Seasoned C-Suite presenter. Excellent leadership skills, with a team-player attitude to drive the end-to-end implementation of use cases under time pressure.
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