We are seeking a Senior Data Scientist to join our marketing team. In this role, you will spearhead Media Mix Modeling (MMM) initiatives aimed at quantifying the impact of our marketing investments and tactics on business outcomes. Your expertise will empower Pinterest's marketing teams to make strategic, confident, and effective investment decisions. By infusing scientific rigor into our measurement and optimization processes, you will play a pivotal role in shaping Pinterest's user growth and marketing strategy. Your contributions will directly influence strategic decisions, such as identifying growth opportunities, understanding user behavior, and defining metrics to sustain and expand our user base.

You will collaborate closely with cross-functional partners across Marketing, Product, Engineering, Analytics, and Data Engineering to address a wide range of business challenges. This role sits within the Growth Marketing team, consisting of three analysts and four data scientists who support various marketing functions, including performance marketing, business marketing, and consumer marketing. As a key member of this team, your primary focus will be on developing MMM solutions tailored specifically for Pinterest Marketing.

What you’ll do:

• Develop end-to-end marketing mix models to evaluate the effectiveness of various marketing channels and campaigns.
• Apply advanced statistical techniques and machine learning algorithms to identify key drivers of user and revenue growth across different marketing channels.
• Build predictive models to forecast the impact of marketing tactics on business outcomes and recommend optimal marketing budgets and strategies.
• Conduct thorough model validation and performance testing to ensure accuracy and reliability of the developed models.
• Present findings and insights to stakeholders in a clear and concise manner, and provide actionable recommendations for improving marketing effectiveness and ROI.
• Develop new statistical models as well as maintain/improve existing models like user lifetime value models.
• Evolve our experimentation capabilities and tools to evaluate the business impact of marketing investments. Advise on experimentation best practices; identifying flaws in experiment practices and results; building tools for experiment analysis; etc. 
• Identify the right measures of success for teams and help them track those metrics. Own the full lifecycle of those metrics from logging requirements, metrics definition, prototype pipelines, and improvements.
• Come up with recommendations for marketing leadership on how we can evolve our internal strategy to address shortcomings, and how we can increase ROI from marketing investments.
• Write clear, actionable analyses that help teams uncover opportunities and identify areas of improvement to our existing strategies. 

What we’re looking for:

• 6+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems.
• Masters degree in a quantitative field such as mathematics, statistics, computer science or engineering.
• Hands on experience with building media mix modeling solutions to quantify the impact of marketing tactics and investments on business outcomes.
• Strong background in statistics, econometrics, and quantitative analysis, with experience in applying advanced statistical techniques to real-world problems.
• Expertise in at least one scripting language (ideally Python/R). Proficiency in SQL/Hive. Ability to write efficient SQL queries.
• Strong business and product sense. Strong skills in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
• Excellent communication skills, able to lead initiatives and communicate findings to the leadership and cross-functional teams. Explains work and thought processes clearly and concisely.
• Experience leading key technical projects.
• Strong Experimentation background.
• Statistical rigor. Experience with causal inference projects.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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