Sr. Data Scientist, Performance Marketing

Description

The team is Growth Marketing, and this role supports performance marketing aimed at growing the user base.

You will bring more scientific rigor into how marketing is measured and optimized, which shapes user growth and marketing strategy.

Your findings will guide company decisions on where to invest for growth, how users grow and behave, and which metrics to track to grow and keep the user base.

You will work with a wide group of partners across Marketing, Product, Engineering, Design, Research, Product Analytics, Data Engineering and other teams.

Interviews involve AI. You will be asked to explain your approach and how you work with AI, with a focus on how you think.

Responsibilities

• Run deep strategic analyses of growth questions, such as how paid performance marketing can drive monthly active users, how to measure its effect in new markets, and how it can lift engagement and lifetime value (LTV).
• Improve existing incrementality tools, including geo-testing frameworks.
• Build and deploy statistical and machine learning models, including propensity, forecasting and LTV models, to improve marketing strategy and audience targeting.
• Create new statistical models and maintain and improve current ones, such as user LTV, budgeting and long-term retention models.
• Partner with Product, Engineering, Analytics, Marketing, Data Engineering and other teams on a range of product and business problems.
• Advance experimentation methods and tools to measure the business impact of paid performance marketing. Advise on best practices, spot flaws in experiments and their results, and build analysis tools.
• Define success measures for teams and help them track them, owning each metric from logging requirements and definition through prototype pipelines and refinement.
• Turn complex analysis into clear, actionable insights and recommendations for technical and non-technical audiences, including senior leaders.
• Write clear analyses that reveal opportunities and show where current strategies can improve.
• Design, maintain and promote dashboards and automated reports so stakeholders can make data-driven decisions on their own. Build and optimize ETL pipelines that automate reporting, support deep-dive analysis and provide features for analytical models.

Requirements

• At least 5 years of combined academic (post-graduate) and industry experience applying scientific methods to real problems.
• A master's degree in a quantitative field such as mathematics, statistics, computer science or engineering.
• Hands-on experience building marketing measurement solutions that quantify the impact of marketing tactics and spend.
• Strong grounding in statistics and quantitative analysis, with experience applying advanced techniques to real problems.
• Expertise in at least one scripting language, ideally Python or R.
• Proficiency in SQL and Hive, with the ability to write efficient queries.
• Strong business and product judgment, with the ability to turn vague questions into defined analyses and success metrics that guide decisions.
• Excellent communication skills. You can lead initiatives, present findings to leadership and cross-functional teams, and explain your work and reasoning clearly and concisely.
• Experience leading key technical projects.
• A strong background in experimentation.
• Statistical rigor, with experience in causal inference projects.

Conditions

The role is US-based only.

Relocation assistance is not offered for this position.

The role requires in-office time for in-person collaboration 1 to 2 times per quarter, and you can live anywhere in the country.

The base salary range is $139,764 to $287,749 USD. The final salary depends on factors such as location, travel, relevant prior experience and specific skills.

The company aims for an equitable, inclusive workplace.

Details on the working model are on the company's PinFlex page.

Benefits

• The position is eligible for equity.
• Details on culture and benefits for this role are published separately.