Minimum qualifications:

　　Bachelor's degree or equivalent practical experience.

　　5 years of experience in program or project management.

　　Experience in supply chain analytics. Preferred qualifications: 10 years of experience in developing and managing supply chain analytics programs.

　　5 years of experience managing cross-functional or cross-team projects.

　　Experience influencing teams and helping the supply chain business prioritize and define value.

　　Understanding of Anylogic or other advanced simulation and modeling tools.

　　Understanding of SQL, Python, and applied Machine Learning.

　　About the job

　　A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Program Manager at Google, you'll lead complex, multi-disciplinary projects from start to finish - working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines.

　　Our goal is to build a Google that looks like the world around us - and we want Googlers to stay and grow when they join us. As part of our efforts to build a Google for everyone, we build diversity, equity, and inclusion into our work and we aim to cultivate a sense of belonging throughout the company.

　　Our team purpose is to enable efficient decision-making across data center supply chain by developing trust and promoting insightful data discovery. We partner cross-functionally to develop, and promote, trusted easy-to-use data, interpretable high-impact analytics, and advanced modeling. We work closely with functional teams across the supply chain (e.g. sourcing, manufacturing, finance, logistics, etc.) to improve data center readiness through data-driven decisions. Our methods range from working on data curation and interactive visualizations through developing machine-learning (ML) models to automate processes. Also, we develop capabilities that enable self-serve analytics in the organization.

　　Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

　　The US base salary range for this full-time position is $136,000-$203,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

　　Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

　　Responsibilities

　　Understand business needs and supply chain design decisions that can enable those needs.

　　Translate supply chain operational process needs into dynamic analytical models which enable business users to make rapid business decisions.

　　Develop and implement intuitive supply chain models and what-if analyses using off the shelf simulation and optimization tools, spreadsheets, or other custom analytical tools to evaluate business scenarios in support of key organizational priorities.

　　Program-manage all aspects of advanced analytics solution delivery (ML models, Statistical models, Optimizations, Simulations) including sprint definition, task prioritization, capacity management and progress tracking including change management efforts by developing documentation, training and webinars to enable self-serve analytics for the supply chain.

　　Develop and lead a portfolio of complex analytic projects (roadmap) and provide technical and program guidance to other analysts and teams.