Sr. Digital Product Manager, Forecasting
New
J
JobgetherResearch & Development
Fully remote work opportunity within the United States., Globally distributed teams across multiple time zones.Full-TimeSenior
Salary$170,958.80–$231,297.20 USD
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Job Details
- Experience
- Doctorate plus 2 years; master’s plus 6 years; bachelor’s plus 8 years; associate’s plus 10 years; or high school diploma/GED plus 12 years.
- Required Skills
- AgileArtificial IntelligenceMachine LearningProduct ManagementData scienceStakeholder management
Requirements
- Bachelor’s degree in Business, Information Systems, Operations, or related field.
- Relevant experience based on education (e.g., 8 years with bachelor’s degree).
- At least 2 years of direct people-management experience or demonstrated leadership experience.
- Proven experience as a digital product leader connecting business strategy, data, and technology.
- Demonstrated success leading data-intensive, analytical, or decision-support products through the full product lifecycle.
- Strong understanding of forecasting, predictive analytics, optimization, simulation, machine learning, or similar analytical capabilities.
- Ability to work effectively with data scientists and technical teams to explain model outputs and limitations.
- Strong knowledge of technology ecosystems, enterprise data platforms, and digital architecture principles.
- Experience applying Agile methodologies within multidisciplinary teams.
- Demonstrated ability to influence senior leaders and navigate competing priorities.
- Exceptional communication and stakeholder-management skills.
- Experience working with globally distributed teams.
Responsibilities
- Translate digital strategy into clear product visions, roadmaps, prioritized backlogs, and measurable outcomes for forecasting and decision-support products.
- Develop a deep understanding of customer workflows, planning challenges, assumptions, and decision-making needs across business functions.
- Identify opportunities where forecasting, optimization, simulation, scenario planning, automation, predictive analytics, and AI-enabled decision support can improve business outcomes.
- Frame complex business challenges as product opportunities that balance customer needs, business value, and technical feasibility.
- Partner with data scientists, engineers, and architects to translate analytical models into intuitive digital products.
- Establish approaches for monitoring model performance, product adoption, and business outcomes.
- Influence senior stakeholders to align teams around a shared product vision.
- Drive product adoption and measure improvements in operational efficiency and decision quality.
- Mentor product managers and contribute to strengthening product management practices across the organization.
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