Uber
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About The Role
Uber Marketplace is at the core of Uber's business, and Rider Pricing & Incentives is a strategically critical component of Marketplace. The mission of the team is to foster growth and improve efficiency of the marketplace through pricing and promotion optimizations. We work on some of the most challenging marketplace problems that impact Uber's top‑line and bottom‑line directly and significantly. We build online and offline systems, leveraging tools from machine learning, optimization, and causal inference. We work in a fast‑paced and collaborative environment.
What You Will Do
Lead both ML and optimization projects to push the frontier of rider pricing/promotion efficiency and optimize the interactions with other marketplace components.
End‑to‑end design and implement ML models and optimization algorithms that convert ambiguous problems into concrete solutions.
Drive end‑to‑end project executions from scoping, offline evaluation, conducting experiments, influencing launch decisions, productionization, and post‑launch monitoring.
Collaborate with cross‑functional partners including product managers and scientists.
Basic Qualifications
5+ years of experience in an ML/optimization role, or 3+ years of experience with a PhD in relevant fields (CS, OR, EE, Stats, etc.).
Expertise in machine learning and optimization algorithms.
Experience with ML frameworks.
Experience with productionizing ML systems.
Proficiency in at least one coding language such as Python, Go, Java, etc.
Strong communication skills and ability to work effectively with cross‑functional partners.
Strong sense of ownership to drive projects end‑to‑end.
Preferred Qualifications
Experience in formulating and solving optimization problems.
Experience in evaluating ML models and overall system in a production environment.
Experience in designing data collection policy for ML models and policy evaluation.
Experience in causal inference and experimental design.
Experience in landing production changes into complex codebases and systems.
Basic understanding of economics concepts.
Compensation
San Francisco, CA‑based roles: base salary USD$198,000–USD$220,000 per year.
Sunnyvale, CA‑based roles: base salary USD$198,000–USD$220,000 per year.
All US locations: eligible for Uber’s bonus program, equity and benefits. More details can be found at https://www.uber.com/careers/benefits.
Seniority level: Mid‑Senior level.
Employment type: Full‑time.
Job function: Engineering and Information Technology.
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About The Role
Uber Marketplace is at the core of Uber's business, and Rider Pricing & Incentives is a strategically critical component of Marketplace. The mission of the team is to foster growth and improve efficiency of the marketplace through pricing and promotion optimizations. We work on some of the most challenging marketplace problems that impact Uber's top‑line and bottom‑line directly and significantly. We build online and offline systems, leveraging tools from machine learning, optimization, and causal inference. We work in a fast‑paced and collaborative environment.
What You Will Do
Lead both ML and optimization projects to push the frontier of rider pricing/promotion efficiency and optimize the interactions with other marketplace components.
End‑to‑end design and implement ML models and optimization algorithms that convert ambiguous problems into concrete solutions.
Drive end‑to‑end project executions from scoping, offline evaluation, conducting experiments, influencing launch decisions, productionization, and post‑launch monitoring.
Collaborate with cross‑functional partners including product managers and scientists.
Basic Qualifications
5+ years of experience in an ML/optimization role, or 3+ years of experience with a PhD in relevant fields (CS, OR, EE, Stats, etc.).
Expertise in machine learning and optimization algorithms.
Experience with ML frameworks.
Experience with productionizing ML systems.
Proficiency in at least one coding language such as Python, Go, Java, etc.
Strong communication skills and ability to work effectively with cross‑functional partners.
Strong sense of ownership to drive projects end‑to‑end.
Preferred Qualifications
Experience in formulating and solving optimization problems.
Experience in evaluating ML models and overall system in a production environment.
Experience in designing data collection policy for ML models and policy evaluation.
Experience in causal inference and experimental design.
Experience in landing production changes into complex codebases and systems.
Basic understanding of economics concepts.
Compensation
San Francisco, CA‑based roles: base salary USD$198,000–USD$220,000 per year.
Sunnyvale, CA‑based roles: base salary USD$198,000–USD$220,000 per year.
All US locations: eligible for Uber’s bonus program, equity and benefits. More details can be found at https://www.uber.com/careers/benefits.
Seniority level: Mid‑Senior level.
Employment type: Full‑time.
Job function: Engineering and Information Technology.
#J-18808-Ljbffr