Uber Staff Scientist Tech 

United States, West Virginia 

995025835

• Undergraduate and/or graduate degree in Statistics, Machine Learning, Operations Research, or other quantitative fields.
• 9+ years of industry experience as an (Applied / Data) Scientist or equivalent.
• Experience with exploratory data analysis, statistical analysis and testing, causal analysis and ML model development.
• Experience in experimental design and analysis.
• Proficiency using Python, Spark at scale with large data sets.
• Experience with tools like SQL, R in a production environment.

• Master’s/Ph.D. Degree in Statistics, Machine Learning, Operations Research, or other quantitative fields.
• Experience in tech or marketplace industries.
• Experienced in partnering with cross-functional stakeholders to execute decisions.
• Ability to mentor, coach and develop junior team members.
• Superb communication and organisation skills.

• Collaborate with Engineering and Product leadership to define the technical vision and guide team direction by identifying opportunities and creating data-driven solutions.
• Design innovative solutions and develop prototypes for business challenges using machine learning and statistical algorithms. Establish and guide data analysis and experimentation frameworks to generate business insights and support decision-making.
• Work closely with Engineering and Product teams to deploy models, improve data observability and metrics, and execute experiments and detailed analyses.
• Design and evaluate A/B tests, switchback experiments and quasi-experiments, applying best practices in experimental methodology to ensure high-quality, unbiased insights.
• Partner with Scientists and Engineers to build and enhance the availability, integrity, accuracy, and reliability of data logging and data pipelines.
• Provide mentorship and technical leadership to other Scientists, promoting a culture of statistical excellence and continuous learning.
• Communicate effectively with leadership and cross-functional teams, presenting the Science team's work on models, solutions, and data analytics outcomes.

* 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 .