Staff Scientist Direct & Connect jobs at Uber

What you'll do:

1. Execute CX Strategy: Lead the execution of comprehensive customer experience strategies that align with business objectives, focusing on enhancing user satisfaction, loyalty, and long-term growth. Drive alignment across regional and global teams to ensure consistent, high-quality experiences at scale.
2. Drive Operational Excellence: Oversee the operational management of customer experience programs. Drive efficiency initiatives, cost management, and process improvements to maximize impact and resource utilization.
3. Lead Cross-Functional collaboration: Foster strong partnerships with key departments (e.g., Ops, Product, Tech, Business, Global teams) to align on customer experience initiatives. Act as a strategic liaison to ensure seamless execution and cross-departmental synergies in delivering customer-focused outcomes.
4. Champion Customer-Centric strategy across the Organization: Advocate for customer-centric initiatives within strategic discussions, ensuring that customer needs and feedback are central to decision-making.
5. Leverage Data to Inform Strategy & Operational Decisions: Utilize data and analytics to measure the effectiveness of CX strategies and operational performance. Provide actionable insights to refine and adapt strategies, identify opportunities for operational improvements, and support business growth.
6. Monitor Program Performance & Report on Results: Regularly assess program performance against KPIs and business objectives. Provide senior leadership with insights on progress, challenges, and opportunities, ensuring timely adjustments to keep programs on track.
7. Align Global and Regional Teams for Scalability: Ensure alignment between global and regional teams to scale customer experience operations efficiently. Support localization efforts where necessary while maintaining a consistent experience across markets.

Basic Qualifications

1. Program Management expertise: 5+ years of experience leading complex, cross-functional programs with a proven track record of flawless execution and delivering meaningful business outcomes.
2. Product Development leadership: Demonstrated success in driving product development initiatives from concept through launch. Deep understanding of the product lifecycle, strong collaboration with Tech teams, and hands-on experience with agile methodologies.
3. Stakeholder Management: Skilled in influencing and aligning cross-functional teams. Strong ability to navigate organizational dynamics to build consensus and drive shared goals.
4. Strategic Thinking & Problem Solving: Proven ability to think strategically and solve complex challenges. Skilled at developing actionable strategies that support both short-term execution and long-term growth, with a focus on operational efficiency and adaptability in fast-changing environments.
5. Digital Customer Experience : In-depth knowledge of omnichannel experience design and optimization—including chat, email, phone, social, in-app messaging, and other digital platforms—to enhance the end-to-end customer journey.
6. Data-Driven Decision Making: Advanced analytical skills with the ability to interpret customer insights, NPS/CSAT metrics, and behavioral data to define strategies. Experienced in using dashboards, reporting tools, and customer data platforms to drive performance.
7. Voice of the Customer (VoC) Programs: Experienced in designing and scaling VoC programs to systematically capture, analyze, and act on customer feedback across all touchpoints—closing the loop between insight and action.
8. Customer-Centric mindset: Deeply committed to delivering world-class customer experiences and embedding customer-centric thinking into team culture and strategic decision-making. Advocates for the customer at every level of the organization.
9. Well developed communication: Skilled in crafting and delivering clear, compelling communications—across presentations, written content, and everyday interactions—to effectively inspire, inform, and align stakeholders at all levels. Adept at tailoring messages to diverse audiences to drive clarity, engagement, and action.
10. Multilingual Fluency: Fluent in English and Spanish; working proficiency in Portuguese is a plus.
11. Location Requirement: Must be available to work onsite at our Mexico or Sao Paulo office.

Preferred Qualifications

1. Experience in Tech or High-Growth Environments: Background in fast-paced tech companies (e.g., Amazon, Meta, Uber, DiDi, etc.) where customer-centricity, operational excellence, and agility are critical. Experience navigating complex organizational structures and delivering results at scale.
2. SQL & Data Literacy: Working knowledge of SQL and data analysis tools to independently query, analyze, and visualize customer data. Ability to partner effectively with Data/BI teams to inform decision-making and uncover insights.
3. Agile Program Management: Solid understanding of Agile principles and experience working within Agile or hybrid environments. Comfortable collaborating with Product and Engineering teams using frameworks like Scrum or SAFe.
4. Global or Cross-Cultural Team Management: Experience working in or leading teams across different cultures, time zones, and business contexts. Sensitivity to cultural nuances and the ability to adapt communication and leadership style accordingly.

* Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to .

You’ll tackle some of the most complex problems in applied machine learning: real-time pricing optimization, supply-demand balancing, and driver behavior modeling at unprecedented scale. Your work will involve cutting-edge techniques including causal inference, reinforcement learning, algorithmic game theory, and multi-objective optimization to solve challenges that don’t exist anywhere else in the industry.

As a Senior Staff ML Engineer reporting directly to the Engineering Director, you’ll drive technical strategy, mentor senior engineers, and establish ML engineering excellence across the Driver Pricing organization while solving problems that directly impact tens of billions of dollars in marketplace transactions.

Technical Leadership & Innovation

• Lead the design and implementation of advanced ML systems for dynamic pricing algorithms serving millions of drivers across 70+ countries around the world
• Architect real-time ML infrastructure handling 1M+ pricing decisions per second with sub-50ms latency requirements
• Drive breakthrough research in causal ML, reinforcement learning, algorithmic game theory, and multi-objective optimization for marketplace optimization with strategic agents
• Own end-to-end ML model lifecycle from research through production deployment and continuous optimization

Platform & Architecture

• Build scalable ML architecture and feature management systems supporting Driver Pricing and broader Marketplace teams
• Design experimentation frameworks enabling rapid testing of pricing algorithms using A/B, Switchback, Synthetic Control, and other experimental methodologies
• Establish ML engineering best practices, monitoring, and operational excellence across the organization
• Create platform abstractions that enable other ML engineers to iterate faster on pricing algorithms

Cross-Functional Impact

• Partner with Product, Operations, and Earner Experience teams to translate complex business requirements into ML solutions
• Collaborate with Marketplace Engineering and Science teams to productionize cutting-edge ML research
• Work with Platform Engineering teams to ensure ML systems meet reliability and performance standards
• Influence technical roadmaps across multiple teams through technical leadership and strategic thinking

Team Development

• Mentor and grow senior ML engineers, establishing technical standards and engineering culture
• Lead technical discussions and architecture reviews for complex ML systems
• Drive knowledge sharing and technical excellence across the Driver Pricing engineering organization

• PhD in Computer Science, Machine Learning, Operations Research, or related quantitative field OR Master’s degree with 12+ years of industry experience
• 10+ years of experience building and deploying ML models in large-scale production environments
• Expert-level proficiency in modern ML frameworks (TensorFlow, PyTorch, JAX) and distributed computing platforms (Spark, Ray)
• Deep expertise across multiple areas including: Deep Learning, Causal Inference, Reinforcement Learning, Multi-objective Optimization, Algorithmic Game Theory, and Large-scale Ads Ranking/Auction Systems
• Proven track record of leading complex ML projects from research through production with significant measurable business impact
• Strong programming skills in Python, Java, or Go with experience building production ML systems
• Experience with feature engineering, model serving, and ML infrastructure at scale (handling millions of predictions per second)
• Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives

• Marketplace or two-sided platform ML experience with understanding of supply-demand dynamics and pricing mechanisms
• Publications or patents in applied machine learning, particularly in areas relevant to optimization, pricing, or marketplace dynamics
• Experience with causal inference methodologies and their application to business problems with network effects
• Reinforcement learning experience in production environments with long-term optimization and strategic agent considerations
• Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives
• Experience with real-time ML systems requiring low-latency inference and high-throughput model serving
• Background in economics, operations research, or related quantitative disciplines with application to marketplace problems
• Experience with Ads ranking and auction systems with strategic bidding agents and real-time optimization

Required:

• Advanced Deep Learning and Neural Network architectures
• Scalable ML architecture and distributed model training
• Feature engineering and real-time feature serving
• ML model deployment, monitoring, and lifecycle management
• Statistical analysis and experimental design for ML systems
• Causal Machine Learning and causal inference methodologies
• Reinforcement Learning and Multi-Armed Bandits
• Multi-objective optimization and Pareto efficiency
• Algorithmic Game Theory for strategic agent modeling

Preferred:

• Personalization and ranking systems at scale
• Time series forecasting and demand prediction
• Graph-based ML for network effects modeling
• Experience with Ads ranking and auction systems

For New York, NY-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.

About the Role

Your primary mission will be to architect a world-class search ecosystem for all Uber employees. This requires a dual-pronged technical strategy: leading the in-house development of novel AI components while also conducting deep evaluations of cutting-edge third-party solutions. You will be the key technical decision-maker on when to build and when to integrate.

- - - - What the Candidate Will Do ----

1. Architect the Ecosystem: Design and own the technical vision for Uber's next-generation enterprise search platform, creating a cohesive strategy that integrates first-party AI models with best-in-class third-party technologies.
2. Lead AI Implementation: Drive the exploration and implementation of advanced AI capabilities. This includes architecting conversational interfaces, enabling multi-step reasoning, and bringing agentic AI functionalities to our users, whether through in-house development or strategic integration.
3. Make Critical Build-vs-Buy Decisions: Conduct deep technical evaluations of industry-leading AI solutions. You will own the process of vetting vendors, prototyping integrations, and providing clear recommendations to leadership.
4. Lead and Mentor: Lead a world-class team of software and machine learning engineers. Provide technical guidance, conduct architectural reviews, and foster a culture of innovation and engineering excellence.
5. Build and Integrate: Remain hands-on, writing production-quality code for critical custom components, integration layers, and core platform infrastructure.
6. Collaborate and Influence: Work closely with senior leadership, product managers, and stakeholders across the company to define the roadmap and ensure your team's work aligns with Uber's strategic goals.

- - - - Basic Qualifications ----

1. Bachelor's degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
2. 8+ years of professional experience in software engineering, with a proven track record of shipping complex.
3. Strong programming proficiency in Python and experience with systems programming languages (e.g., Go, Java, C++).
4. Significant experience in designing and building production systems leveraging machine learning, especially in Search, NLP, or Conversational AI.
5. 2+ years of experience in a formal or informal technical leadership role, including mentoring engineers and setting technical direction for a team.

- - - - Preferred Qualifications ----

1. Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2. Experience architecting systems that involve Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and vector databases.
3. Demonstrated experience making strategic build-vs-buy decisions and integrating large-scale third-party software or SaaS platforms into a complex enterprise environment.
4. Experience with the architecture of AI agentic systems or complex, multi-step LLM-powered workflows (either through building or integration).
5. Expertise with both traditional search technologies (e.g., Elasticsearch) and modern semantic search paradigms.
6. Excellent communication skills, with the ability to articulate complex technical trade-offs to diverse audiences and influence technical strategy at a senior level.
7. A strong product intuition and a passion for creating user-centric AI experiences that solve real-world problems.

* Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to .

What You Will Do

1. Develop data-driven business insights and work with cross-functional customers to find opportunities and recommend prioritization of product, growth, and optimization initiatives.
2. Build statistical, optimization, and machine learning models for strategic insights as well as in production enhancements to the membership program.
3. Design and analyze experiments, present results that provide actionable recommendations.
4. Orient our teams around data-driven product development by driving the creation of logging, metrics, data visualization and diagnostic tools, and experimentation paradigms.
5. Define how our teams measure success, by developing metrics, in close partnership with cross functional partners.

- - - - Basic Qualifications ----

1. Ph.D., M.S. or Bachelor's degree in Statistics, Economics, Mathemathics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
2. 4+ years of industry experience as an Applied or Data Scientist or equivalent (or 2+ years with Ph.D.).
3. Background in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl)
4. Coding and SQL proficiency and ability to develop statistical analysis and algorithm prototyping in Python or R.
5. Ability to use Python, SQL, R or similar technologies to work efficiently with large data sets
6. Design experiments and interpret the results to draw detailed and actionable conclusions across a variety of key performance indicators

- - - - Preferred Qualifications ----

1. Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams
2. Experience leading key technical projects and substantially influencing the scope and output of others
3. Knowledge of experimental design and analysis or experience with exploratory data analysis and model development
4. Experience communicating qualitative research methods and findings to non-qualitative researchers
5. Track record of engaging senior leadership effectively to build understanding of and consensus for the viewpoints of the team
6. Solid theoretical and applied ML skills and a strong background in mathematics and stats
7. Solid Programming skills to prototype models in at least one of Python (preferably), R, Java, Go, Scala
8. Expert in one of the following areas: Deep learning, ML System Design, A/B experimentation design, Causal Inference
9. Experience of working with large dataset using Spark, Hive, HDFS is desired
10. Analyze large data sets to identify behavior trends among good users and bad actors, using statistics, data mining, and machine learning techniques
11. Thought leadership to drive multi-functional projects from concept to production

For San Francisco, CA-based roles: The base salary range for this role is USD$183,000 per year - USD$203,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link .

What the Candidate Will Do:

1. Serve as a technical leader on our most demanding, cross-functional projects.
2. Functionally decompose complex problems into simple, straight-forward solutions.
3. Mentor and grow other eng leaders on the team and in the org
4. Possess expert knowledge in performance, scalability, enterprise system architecture, and engineering best practices.
5. Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues and helping managers guide the career growth of their team members
6. Exert technical influence over the App Experience team, increasing the team's productivity and effectiveness by sharing your deep knowledge and experience. You are a visionary leader, builder and an operator.
7. Balance technical leadership and savvy with strong business judgment to make the right decisions about technology choices.

Basic Qualifications:

1. Minimum 7 years of software engineering experience
2. Strong product-focused engineer with past consumer product expertise
3. Experience leading teams of other product-minded engineers, while also contributing to the roadmap across IC dimensions
4. Mastery of object-oriented design, data structures, distributed systems, and algorithms

Preferred Qualifications:

1. Deep hands-on technical expertise in at least one major technical area: large scale full stack development, building complex distributed systems, launching complex UX overhauls
2. Experience working with personalization and recommendation systems to craft rich, cohort-based experiences for users
3. Domain knowledge of marketplace systems
4. Strong cross-functional collaboration and team bar-raising skills

For New York, NY-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

About the Role

- - - - What the Candidate Will Do ----

1. Use data to understand product performance and to identify improvement opportunities.
2. Build statistical, optimization, and machine learning models for a range of applications in the pricing and incentives algorithms space.
3. Design and execute product experiments and interpret the results to draw detailed and actionable conclusions.
4. Present findings to senior management to inform business decisions.
5. Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productionization

- - - - Basic Qualifications ----

1. Ph.D., M.S., or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields.
2. 2+ years of experience as an Applied or Data Scientist or equivalent (can be also as part of Ph.D training).
3. Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics.
4. Experience in experimental design and analysis.
5. Experience with exploratory data analysis, statistical analysis and testing, and model development.
6. Ability to use Python to work efficiently at scale with large data sets.
7. Proficiency in SQL.

- - - - Preferred Qualifications ----

1. 2+ years of industry experience.
2. Experience in algorithm development and prototyping.
3. Experience in pricing optimization.
4. Experience with productionizing algorithms for real-time systems.
5. Well-honed communication and presentation skills.

For New York, NY-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year.

About the Role

As a Staff Application Engineer-TLM on our Atlassian team, you will be responsible for the architectural integrity and operational excellence of our entire Atlassian suite, including Jira, Confluence, and Jira Service Management. You will ensure the technical foundations of our platforms are operating optimally and that the data and interfaces consumed by our internal teams meet the highest quality standards.

You will partner with a talented team of engineers, Business Systems Analysts (BSAs), Product Managers, business leaders and other stakeholders to define joint requirements and deliver outcomes that create seamless experiences for our internal employees worldwide. Atlassian TLMs have multifaceted roles: they not only significantly influence a broad range of business and technology choices but also actively engage in the engineering and execution of technical solutions. You will be responsible for exploring and incorporating the
latest trends in AIto solve critical customer problems.

- - - - What the Candidate Will Do ----

1. Leadership & Strategy
2. Provide technical leadership and mentorship to a multi-pod team of 10+ application developers and BSAs .
3. Act as a role model for the team, demonstrating good judgment and responsibility.
4. Drive the strategic roadmap for the Atlassian platform, aligning with the broader vision of the organization.
5. Helping with Hiring Atlassian admins, App Developers and coach/enable them to enhance their skills as BSAs
6. Ability to build the team and enable it to be high performing
7. Be a trusted advisor for team members and leadership, helping the team navigate differences of opinion to commit and move forward.
8. System Analysis
9. Analyze complex business requirements to understand the specific needs of the organization.
10. Identify areas where process automation, custom development, or AI-powered solutions can add significant value, improving efficiency, relevance, and user satisfaction.
11. Solution Design & Architecture
12. Design and architect robust, scalable, and cost-efficient solutions across both Atlassian Data Center and Cloud , often in a co-hosted, multi-instance environment.
13. Drive strategic initiatives that enable the platform to scale with heavy usage and complex integrations.
14. Evaluate marketplace applications against custom-built solutions to meet business needs effectively.
15. Propose and implement solutions that optimize licensing costs across the portfolio.
16. Atlassian Configuration & Custom Development
17. Oversee the development of custom scripts, plugins, and integrations using tools like Groovy, the Atlassian SDK, Forge, and REST APIs.
18. Guide the team in creating and modifying complex workflows, automations, and custom fields to support business processes.
19. Implement personalization features based on user roles, preferences, and history.
20. Platform Health & Operational Excellence
21. Maintain a strategic overlook of service health, scale, availability, and reliability to ensure platform stability.
22. Drive operational excellence by building quick, efficient solutions to immediate problems while planning for long-term health.
23. Monitor and analyze system performance, optimizing resource consumption and response times.
24. Testing and Validation
25. Develop and execute comprehensive test plans to validate platform solutions, automations, and integrations.
26. Troubleshoot and resolve complex issues related to platform functionality and performance.
27. Security and Compliance
28. Ensure all Atlassian implementations adhere to strict security and compliance standards, especially when handling sensitive data.
29. Define and enforce access controls, roles, and security settings for users.

- - - - Basic Qualifications ----

1. 12+ years of progressive experience in the Atlassian ecosystem , with a strong focus on application architecture.
2. 3+ years of people management experience , with a proven ability to lead and mentor technical teams.
3. 2+ years of hands-on experience in designing and incorporating AI solutions to enhance platform capabilities.
4. Expert-level architectural experience with Atlassian Data Center and Atlassian Cloud , including managing complex, multi-instance solutions of Jira, JSM, and Confluence.
5. Proven ability to work closely with stakeholders at all levels (PMs, Leadership, Business) to align on requirements and deliver solutions.
6. Deep knowledge of the entire Atlassian marketplace ecosystem and solution providers.
7. Experience managing and working with larger teams in a vendor-rich environment.
8. Excellent written and verbal communication skills.

- - - - Preferred Qualifications ----

1. Architectural experience with Asana is a plus .

* Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to .