Applied Scientist II
Uber · New York, NY
- On site
- Full-time
- $170,000 / year
- New York, NY
Job highlights
- Optimize brand marketing budget with data-driven insights.
- Apply statistical methods to measure marketing impact.
- Develop and improve marketing technical tools.
- Collaborate with cross-functional teams and external partners.
- Guide business and marketing strategy with actionable insights.
About the role
About The Role
We're looking for an Applied Scientist to join our Brand Science team to provide strategic, actionable insights around how to measure and optimize a large brand marketing budget. In the role, you'll be part of and collaborate with a cross-functional team consisting of marketing/media stakeholders, our in-house research and insights team, as well as other scientists across the broader organization.
Problems We're Working On Include
- How do we measure the impact of advertising on television and billboards?
- Can we find a better way to allocate our brand budget across a diverse set of advertising platforms, marketing initiatives, and audiences?
- How can we improve our existing measurement tools to improve sensitivity and reduce bias?
The ideal candidate is both technically deep and intellectually humble. You enjoy out-of-the-box thinking, and are not afraid to roll up your sleeves to get things done. You prioritize practical solutions over novelty but stay curious about new methods and their tradeoffs. You focus on tangible progress and results, but also have a generous spirit, giving others the benefit of the doubt and actively seeking to understand their perspectives.
What You'll Do
- Apply statistical/econometric methods to estimate the incremental impact of changes in marketing and product strategy on brand-relevant KPIs like sentiment, awareness, and purchase intent - as well as on business outcomes like trips/orders and gross bookings.
- Build and improve technical tools for marketing problems. Examples include media mix models, statistical estimators to gauge the impact of various interventions (experimental or otherwise), optimization engines that determine how to best distribute resources, etc.
- Interface closely with external partners (media agencies, advertising platforms, measurement vendors) to deeply understand the existing capabilities and limitations of their platforms and solutions, and to push the envelope on what is possible.
- Collaborate with our in-house media, research, product, and operations teams to develop actionable customer insights and recommendations to guide high level business and marketing strategy.
Basic Qualifications
- Ph.D., M.S., or B.S. degree in Statistics, Computer Science, Applied Mathematics, Electrical Engineering, Economics, or other quantitative fields is preferred. (If M.S. degree, a minimum of 2+ years of industry experience required, if B.S. degree a minimum of 3+ years of industry experience required)
- Advanced skills in SQL, Python, and BI tools for data analysis/visualization
- In-depth understanding of and experience with experimental design
Preferred Qualifications
- Experience with solving quantitative problems in the marketing/AdTech space
- PhD in a quantitative field such as statistics, economics, or operations research
Key skills/competency
- Applied Scientist
- Brand Science
- Marketing Budget Optimization
- Statistical Modeling
- Econometrics
- Media Mix Models
- Experimental Design
- Data Analysis
- Python
- SQL
Skills & topics
- Applied Scientist
- Data Science
- Marketing Analytics
- Brand Marketing
- Econometrics
- Statistical Modeling
- Python
- SQL
- Uber
- AdTech
How to get hired
- Tailor your resume: Highlight your quantitative skills, statistical modeling, and marketing experience.
- Showcase your projects: Demonstrate experience with SQL, Python, and experimental design.
- Prepare for technical questions: Be ready to discuss econometrics, media mix models, and data analysis.
- Emphasize collaboration: Highlight your ability to work with diverse teams and external partners.
- Understand the role: Focus on how you can optimize brand marketing budgets and drive business outcomes.
Technical preparation
Practice SQL for data extraction and manipulation.,Review Python libraries for data science.,Study statistical and econometric modeling concepts.,Prepare to discuss experimental design principles.
Behavioral questions
Describe a time you solved a complex problem.,How do you handle ambiguity in projects?,Tell me about a collaborative team experience.,How do you prioritize practical solutions over novelty?
Frequently asked questions
- What are the key responsibilities for an Applied Scientist II at Uber?
- As an Applied Scientist II on Uber's Brand Science team, you will apply statistical and econometric methods to measure marketing impact, build technical tools like media mix models, and collaborate with cross-functional teams to provide actionable insights for marketing strategy.
- What qualifications are essential for the Applied Scientist II role at Uber?
- Essential qualifications include a Ph.D., M.S., or B.S. in a quantitative field, advanced SQL and Python skills, and a strong understanding of experimental design. Prior industry experience is also required depending on the degree obtained.
- What is Uber looking for in an ideal candidate for the Applied Scientist II position?
- Uber seeks candidates who are technically deep, intellectually humble, enjoy out-of-the-box thinking, and prioritize practical, results-oriented solutions. A generous spirit and ability to understand others' perspectives are also valued.
- How does Uber use data science in its brand marketing efforts?
- Uber utilizes data science to measure the impact of advertising across various platforms, optimize budget allocation, improve measurement tools, and provide strategic recommendations to guide marketing initiatives and business outcomes.
- What kind of problems does the Brand Science team at Uber address?
- The Brand Science team tackles problems such as measuring advertising impact on TV and billboards, optimizing brand budget allocation across diverse platforms, and enhancing the sensitivity and reducing bias in existing measurement tools.
- Is there specific experience preferred for the Applied Scientist II role at Uber?
- Preferred qualifications include experience with quantitative problems in the marketing/AdTech space and a PhD in a quantitative field like statistics, economics, or operations research.
- What is the typical career progression for an Applied Scientist at Uber?
- While specific progression paths vary, an Applied Scientist II role at Uber offers opportunities to grow into more senior scientific roles, lead complex projects, and contribute to high-level strategic decisions within the brand science domain.
- How can I best prepare my application for the Applied Scientist II role at Uber?