Principal Product Scientist - SMB Labs

Key Skills

Java Programming, Python Programming, SQL, Machine learning techniques, Data science techniques, A/B Testing, Data Modeling, R Programming, Statistics, Data Engineering, Data Analysis

Job Description

We are seeking a Principal Product Scientist to partner with the senior director of product in the development of a brand new mobile app connecting job seekers directly to hiring managers through chat. In this role, you will use your skills in causal analysis, experimentation, and machine learning combined with a strong business sense to to ask and answer questions that will lead to future versions of our product. In this role, you will influence scientists, product managers, and engineers across multiple organizations within Indeed.

Product Science advances data-driven decision-making using the scientific method on Indeed’s products. In the Data Science organization, the Product Scientists are embedded working closely with Product Managers and their Engineering teams. Both Product Scientists and Product Science Managers are a mixture of a statistician, scientist, machine learning expert, and a product leader. Principal Product Scientists maintain the overall science vision and establish clear purposes and goals of the product area and drive cross-team science and analytics initiatives.

Learn more about Product Science at Indeed

About You

You're someone who wants to see the impact of your work making a difference every day. You understand how to use data to make decisions and how to train others to do so. You have delivered challenging technical solutions at scale. You have influenced Data Science or Product teams, and earned the respect of talented practitioners. You are equally happy talking about causal inference and operational research, as you are brainstorming about practical experimental design and product strategy. You love being in the mix technically while providing impactful mentorship to your teams.

Responsibilities

• Use scientific method to formulate product hypotheses, experiments to to evaluate those hypotheses, and methods to measure performance of Indeed products through rigorous statistical analysis
• Identify new opportunities by studying customer data intently. Cultivate a deep understanding of the product space as well as the raw data related to it. 
• Work alongside product managers and other cross-functional leaders to help guide tactical and strategic product decisions across multiple teams, using statistically sound approaches
• Mentor other scientists, product leads and engineers across teams
• Break down larger investigations that no single team can accomplish on their own into pieces that deliver incremental business value and lead the teams to execute on them
• Be a part of new business organization, influencing a science driven decision culture, crafting a science strategy and laying the groundwork for next generation of advertising systems at Indeed

Who You Are

Requirements

• 10+ years of professional industry experience in Data Science, Business Analytics, or Data Analysis (or 7+ with a PhD or MS).
• 10+ years of experience in a programming language like R or Python, and a query language (eg SQL)
• Deep knowledge of statistical measurement techniques like AB or bandit testing, causal inference, and propensity modeling
• Experience developing machine learning models
• Experience designing and conducting complex and ambiguous data science or analysis projects.
• Strong sense of ownership as a technical and product leader
• Ability to write and present results to both technical and business audiences
• Experience mentoring others
• Have a passion to develop product and science strategy based on deep insights from the data

What we’d love to see (but isn’t required):

• Background Master’s or PhD., with advanced coursework in statistics, economics, and operations research.
• Experience with applying state of the art A/B testing methods or other causal inference and experimental approaches.
• Experience with estimating customer lifetime value and tying product goals to long term business value