Sr Manager - Uber Eats Promotions & Incentives
Uber - Sunnyvale, California, United States, 94087![Uber](/api/image?src=https%3A%2F%2Fgeneral-board-default.s3.us-east-2.amazonaws.com%2Fpublic%2Fimages%2Fdesk-360x180.webp&w=640&q=75&f=webp)
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Have you got what it takes to succeed The following information should be read carefully by all candidates.With technical and leadership expertise, you will be a Senior Engineering Manager within the Eats marketplace organization, responsible for leading teams in the space of consumer pricing, engagement, and incentives for Uber Eats. You will manage project priorities, deadlines, and deliverables, mentor and coach team members, and help enhance their skill set. You will work with product owners, data scientists, and business teams to translate key insights and business opportunities into solutions, support productionization efforts, and empower the team to deliver impact.What the Candidate Will Do:Lead engineering team in the space of consumer pricing, engagement, and incentives for Uber Eats.Manage project priorities, deadlines, and deliverables.Partner with product owners, data scientists, and business teams to translate key insights and business opportunities into solutions.As a technology leader with hands-on experience, develop a team with deep technical skills; coach and mentor individual contributors.Basic Qualifications:Bachelor’s Degree or equivalent in Computer Science, Engineering, Mathematics, or related field.9+ years full-time work experience in software engineering and/or product development.5+ years full-time Engineering Management work experience.Ability to problem-solve and make complex decisions with incomplete information in dynamic marketplace environments.Great interpersonal skills, deep technical ability, and a track record of successful execution in cloud-scale product development.Preferred Qualifications:Master’s degree or PhD in Computer Science, Engineering, or a related technical field.Minimum 5 years of hands-on experience in developing machine learning or deep learning solutions for real-world problems.3+ years of experience working in a complex, matrixed organization involving cross-functional, and/or cross-business projects.Industry experience in one or more of the following: Reinforcement Learning, Bayesian Optimization, Multitask Learning.Experience leading backend platform and ML engineering teams, with hands-on engineering experience in at least one of these domains.5+ years of progressive management leadership experience directing high visibility initiatives in geo-distributed team environments.An inspirational technical leader with a high emotional intelligence who sets high and exacting standards and demands the best work of their team.Proven track record of growing and mentoring accomplished staff ICs and EMs.For San Francisco, CA-based roles: The base salary range for this role is USD$252,000 per year - USD$280,000 per year.For Sunnyvale, CA-based roles: The base salary range for this role is USD$252,000 per year - USD$280,000 per year.For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of compensation. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
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