Applied Scientist IIData Scientist, Data Science San Francisco, California | New York, New York Full Time

About the RoleWe're looking for an Applied Scientist to join our Brand Science team and provide strategic insights, measurement, and optimization for a large brand marketing budget. In the role, you'll be part of and collaborate with a cross-functional team consisting of marketing, research, media and creative. As a member of the brand science team, you will not only be able to perform complex analyses exploring our large and rich dataset, but also shape marketing and measurement strategy. You'll play a big role in finding opportunities to help the marketing function scale as we develop the global Uber brand.

As an Applied Scientist, you will work on the most technically challenging projects of the science team, tackling complex causal inference questions and designing intricate experiments.

Problems we're working on include:

How long can we run a creative asset before it hits diminishing returns due to wear out?

What is the long-term impact of brand marketing and can we quantify it?

What is the most effective way to target users of strategic interest?

What are the most signal-rich proxies to use for optimization?

The ideal candidate combines deep experimentation and inference knowledge with outstanding stakeholder management skills and strong business acumen to help align learning agendas with strategic priorities. You are skilled in translating a stakeholder's questions into a data-based analysis or experimentation plan, clarifying the question we want to answer and identifying the right data to answer exactly that question.

What You'll DoDesign measurement and optimization for a large brand marketing budget, using a toolset ranging from experimentation to survey-based methods and causal inference

Work closely with our media, research and marketing teams to develop actionable customer insights and recommendations to guide high level marketing strategy and inform improvements through the course of the campaign lifecycle

Leverage rich internal databases to mine patterns on winning marketing tactics and understand customer behavior to inform marketing briefs

Leverage causal inference models for advanced campaign measurement and optimization

Tackle open-ended questions about marketing effectiveness, interaction effects, incrementality & related topics

Regularly present insights and learnings to executive leadership

Basic QualificationsPh.D., M.S. or Bachelors degree in Statistics, Economics, Mathematics, Operations Research, or other quantitative fields

Experience with data analysis and visualization tools, such as Python, R

Experience with SQL on large multi-table data sets

In-depth understanding of and experience with experimental design

Familiarity with causal inference and econometrics techniques to measure incrementality

• Preferred QualificationsIntellectual curiosity and a demonstrated ability to provide thought partnership to executive stakeholders
• Excellent communication skills to understand stakeholder needs, set expectations around feasibility, translate business challenges into research questions, and present findings to non-technical audiences
• Ability to translate data science findings into strategy

Experience identifying and adapting to imperfect data

Experience with marketing analytics, marketing measurement or market research - including survey-based measurement tools

Understanding of capabilities offered by publishers including ad products, brand lift and measurement solutions

Someone who is willing to contribute new ideas and articulate them to a variety of business partners and not just execute on existing ones

The ability to balance attention to detail with swift execution, including the ability to deliver on tight timelines