Test Program Development Engineer Manager Manager Manager Manager Manager Manager Consultant in San Francisco

A Test Program Manager (or Test Engineering Program Manager) leads cross-functional teams to define, plan, and execute product testing strategies, ensuring quality from development to launch. They manage test schedules, budgets, and vendor relations while driving bug resolution and reporting status to leadership. Apple +4 Key Responsibilities Strategy & Planning: Define comprehensive end-to-end testing strategies, covering functional, regression, and system testing. Cross-Functional Leadership: Coordinate with software, hardware, and RF test engineers to align testing with product development. Execution & Monitoring: Drive test readiness reviews, monitor test execution, and manage defect reporting. Vendor & Budget Management: Manage test suppliers, vendors, and development budgets. Risk Management: Proactively identify project risks, inter-dependencies, and bottlenecks to ensure on-time delivery. Apple +6 Required Skills & Qualifications Technical Proficiency: Familiarity with test technologies, CICD, and automation tools. Project Management: Experience with software development lifecycles (SDLC) and complex product testing. Communication: Excellent leadership, presentation, and conflict-resolution skills. Education/Experience: Often requires a degree in Engineering (Software/Electrical) and experience in testing or program management. Apple +4

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. We’re looking for a proactive, collaborative Manager of Internal Audit to help execute our internal audit program and support Lyft’s governance, risk management, and compliance efforts. This role will focus on both business and technology audits, helping identify and address key risks while delivering insights that enable informed decision-making. Reporting to the Director of Internal Audit, and based in our San Francisco HQ, you’ll work closely with stakeholders across the company to strengthen controls, improve processes, and drive continuous improvement. Responsibilities: Audit Execution & Risk-Based Planning Execute audit and advisory engagements spanning across both technology (e.g. cybersecurity, data governance, infrastructure, etc.) and business (e.g. operations, compliance, etc.) domains from end to end — including planning, fieldwork, testing, and reporting. Perform annual risk assessment over assigned risks to develop and refine the annual risk-based audit plan. Take a hands-on approach to audits, ensuring findings are data-driven, relevant, and aligned with business objectives. Use process improvement techniques (e.g. process mapping, root cause analysis, gap assessments) to identify opportunities for enhanced control design and operational efficiency. Perform risk assessments and identify areas for process improvement, control enhancement, or technology enablement. Ensure timely and effective follow-up on remediation of audit findings, coordinating with business owners to verify resolution. Collaborate with cross-functional teams — including Engineering, Security, Legal, Finance, and Compliance — to assess risks and test key controls. Stay current on evolving risks related to emerging technologies, regulatory changes, and internal initiatives. Enterprise Risk Management (ERM) Support

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Lifecycle Growth Marketing team engages with millions of Lyft riders and drivers to drive preference and usage of Lyft. The team runs hundreds of acquisition, engagement, retention and resurrection experiments every year across email, push notifications, SMS and in-app messaging surfaces. We are data-driven in everything we do. We test and measure all of our communications and tailor experiences to be personalized and contextual by audience segment. In this role, you will work closely with Product, Engineering, Analytics, Data Science, and Marketing Operations to design, test and optimize incentive and non-incentive messages and experiences. Responsibilities: Own the lifecycle marketing strategy for your audience — define the channel mix, set the prioritization framework, and ensure every communication delivers clear value to the target user Build and manage an experimentation program that drives measurable impact — from ideation through results, with a clear point of view on what to test Partner with Engineering, Product, and Data Science to unlock new platform capabilities, influence roadmaps, and push beyond out-of-the-box tooling Own performance reporting — define metrics, experimentation setup, and share results and next steps with stakeholders and leadership Drive creative strategy — brief, review, and iterate on assets across email, push, SMS and in-app with a strong feedback loop with designers and copywriters Apply behavioral science frameworks to inform message sequencing, timing, and incentive design Experience: 6+ years in growth marketing. You've owned a full lifecycle marketing program from the ground up — not just executing campaigns, but building strategy from high-level goals and managing a prioritized roadmap Strong SQL skills required — you’re comfortabl

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe