Data Scientist Fintech jobs at Uber

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 .

About the role

You will develop automations of varying size and complexity, from medium-scale tasks to large-scale business processes, fully automated end-to-end.

As an Automation Specialist, you will be responsible for building solutions that are resilient, scalable, and adaptable, following best practices and continuously refining them with data-driven improvements.

You will translate business requirements into clear technical tasks, delivering automation solutions iteratively and incrementally, and aligning priorities closely with the Operations Coordinator.

We focus on four core areas:

• Business Processes (design, execution, optimization)
• Automation (process automation, real-time monitoring, refactoring)
• Data Analytics (query, deepdive, self-operating dashboard, data pipeline)
• Data Science (modeling, machine learning, patterns identification, prediction)

What you'll do

• Design, build, and maintain automations to enhance efficiency and scalability
• Streamline workflows, automate entire processes, refactor, build data-pipelines
• Suggest innovative approaches to solve complex business problems, at scale, following the best practices in terms of quality, time management, technical documentation, code review
• Analyze business requirements or suggest improvements, proactively
• Conduct root cause analyses and propose data-driven strategies
• Present your work to Stakeholders and adapt your communication to a variety of audiences, using either technical or business terms

What you'll need

• Good knowledge in Python, with the ability to write code to build self-operating dashboards or automate business action, work with API endpoints and use Pandas Library
• Knowledge in SQL, with the ability to select, clear and transform dataset
• Ability to analyze datasets accurately and storytell
• Knowledge in creating Flows (ex.: uWorc, Lucidchart)
• Analytical and data-driven approach for solving complex problems
• Excellent written and spoken Communication (in English)

• Ability to work on your own initiative independently (proactive), in Group (excellent Teammate) and with Stakeholders

• Motivation to learn all along the way and improve continuously Scripts, with SQL and Python, to automate actions of varying sizes and time-horizons.

* 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 .

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

- - - - What You Will Do ----

1. Design reliable and valid measurement tools to enhance employee listening.
2. Partner with stakeholders on survey design, methodology, and data interpretation.
3. Analyze both active listening (surveys) and passive listening (e.g., organizational network analytics) data to uncover insights on employee motivation, behavior, and experience.
4. Translate complex business problems into data-driven research initiatives with measurable outcomes.
5. Integrate, clean, and analyze people data from multiple sources, applying behavioral science to guide evidence-based decisions.
6. Communicate findings and recommendations to both technical and non-technical audiences to inform key business decisions.
7. Support the planning, execution, and stakeholder engagement of the survey program

- - - - Basic Qualifications ----

1. Master’s or PhD in a quantitative social science field (e.g., Industrial/Organizational Psychology, Educational Psychology, Organizational Behavior, Behavioral Economics).
2. 3+ years of industry experience in People Analytics, consulting, or survey/employee research.

- - - - Preferred Qualifications ----

1. PhD with 3+ years of experience, or Master degree with 4+ years as a survey scientist, applied researcher or data scientist—ideally in the tech industry.
2. Strong background in survey design, psychometrics, and people data analysis.
3. Experience with organizational network analysis (ONA) a plus.
4. Familiarity with I/O psychology and broader people analytics topics.
5. Ability to translate business needs into research solutions and communicate insights clearly.
6. Skilled at managing complex, imperfect, and unstructured people data.
7. Strong project planning and management skills
8. Comfortable with ambiguity, adaptable in fast-paced environments, and innovative in solving complex problems.
9. Demonstrated ownership and ability to lead projects end-to-end

For San Francisco, CA-based roles: The base salary range for this role is USD$140,000 per year - USD$156,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$140,000 per year - USD$156,000 per year.

What You'll Do

• Own the end-to-end lifecycle of scientific models and algorithms, from ideation and development to deployment and iteration, tackling our most complex pricing challenges.
• Act as a thought leader , influencing the product and technical roadmap by identifying new opportunities and translating them into actionable scientific projects.
• Lead the design and analysis of large-scale experiments, pushing the boundaries of causal inference to measure the impact of our pricing strategies and deliver actionable insights.
• Drive collaboration with senior stakeholders across Product, Engineering, and Operations, effectively communicating complex findings and presenting strategic recommendations to leadership.
• Mentor and guide junior scientists on the team, elevating the overall technical bar and fostering a culture of scientific rigor.

What You'll Need (Basic Qualifications)

• A Ph.D. in a quantitative field (e.g., Statistics, Economics, Computer Science, Operations Research) with 2+ years of industry experience, OR a Master's/Bachelor's degree in a similar field with 5+ years of relevant industry experience.
• Deep, hands-on expertise and a proven track record of applying advanced methods from machine learning, statistics, optimization, and causal inference to solve complex, real-world business problems.
• Proven experience leading complex, cross-functional projects, with a track record of influencing the technical direction and output of the team.
• Proficiency in modeling, data analysis, and programming using a language like Python or R.
• Experience querying databases using SQL.
• Excellent communication and presentation skills, with the ability to influence both technical and non-technical audiences.

Preferred Qualifications

• Expert-level knowledge in one or more of the following areas: experimental design, causal inference, machine learning, economics, or optimization, with a track record of designing and implementing model architectures and algorithms.
• Direct experience in a marketplace-related problem space, especially pricing optimization.
• Proven ability to design and analyze large-scale experiments to inform critical pricing and product decisions.
• Experience working with large datasets using distributed computing systems like Spark, Hive, or Presto.

What You'll Do:

1. Refine ambiguous questions and generate new hypotheses about whether marketplace levers such as Rider and Driver Pricing, Matching, Surge etc are functioning appropriately through a deep understanding of the data, our customers, and our business.
2. Define how our teams measure success by developing Key Performance Indicators and other user/business metrics, in close partnership with Product and other subject areas such as engineering, operations, and marketing.
3. Collaborate with applied scientists and engineers to build and improve the availability, integrity, accuracy, and reliability of our models, tables etc.
4. Design and develop algorithms to increase the speed and accuracy with which we react to marketplace changes.
5. Develop data-driven business insights and work with cross-functional partners to find opportunities and recommend prioritization of product, growth, and optimization initiatives

What You'll Need:

1. Undergraduate and/or graduate degree in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative fields.
2. 10+ years of experience as a Data Scientist, Product Analyst, Senior Data Analyst, or other types of data analysis-focused functions.
3. Deep understanding of core statistical concepts such as hypothesis testing, regression, and causal inference
4. Advanced SQL expertise.
5. Experience with either Python or R for data analysis.
6. Knowledge of experimental design and analysis (A/B, Switchbacks, Synthetic Control, Diff in Diff, etc.).
7. Experience with exploratory data analysis, statistical analysis and testing, and model development.
8. Proven track record to wrangle large datasets, extract insights from data, and summarize learnings/takeaways.
9. Experience with Excel and some dashboarding/data visualization (i.e., Tableau, Mixpanel, Looker, or similar).

* 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'll do:

1. Build and maintain dashboards and reports to track key business and sales KPIs, ensuring data accuracy and timely delivery.
2. Develop, test, and maintain machine learning models (e.g., regression models) to estimate Full Potential and share of wallet.
3. Partner with cross-functional teams (e.g., Sales, Strategy, Operations) to translate business questions into analytical projects.
4. Automate data pipelines and reporting workflows to improve efficiency and scalability using SQL, Python, and cloud tools.
5. Analyze trends, identify growth opportunities, and present actionable insights to stakeholders to support strategic decision-making.

What you'll need:

1. A minimum of 4-5 years of experience in a similar role (e.g. BI Analyst, BI Engineer, Data Scientist, Data engineer, Data Analyst, Business Intelligence Engineer, etc.)
2. Strong proficiency in SQL and Python: Hands-on experience in data manipulation, KPI tracking, and building scalable data workflows.
3. Experience developing machine learning models: Regression models used for business forecasting, share of wallet estimation, and opportunity sizing.
4. Proven ability to build and maintain dashboards and reports: Support cross-functional stakeholders with clear, actionable insights through Tableau
5. Experience deploying and operationalizing ML models: Including model monitoring, performance tuning, and integration into business workflows (e.g., via Flask, MLflow, or cloud services)
6. Advanced statistical knowledge: with expertise in techniques like multivariate regression, time series analysis, and A/B testing to drive data-backed strategy.
7. Strong business acumen: Ability to translate complex analytical findings into strategic recommendations, especially in sales performance and market share contexts.
8. Cloud platform experience (GCP, AWS, or Azure): Particularly working with data warehouses like BigQuery or Snowflake to scale data processing and model training.

* 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 .