Founding Data Scientist, Marketing Analytics

Salary: $150K - $200K Location Type: Remote Employment Type: Full-Time

Company Overview

Kindred is a members-only home swapping network that unlocks the ability to live a travel-rich lifestyle through the power of community. By exchanging primary residences with trusted peers, renters and owners alike can match with Kindred spirits and explore new destinations without breaking the bank.

We are on a mission to build a sharing economy that lives up to the name, and we’ve raised significant capital from some of the best investors in Silicon Valley, including Index Ventures, Andreessen Horowitz, New Enterprise Associates, Bessemer Venture Partners, Caffeinated Capital, Elad Gil, and the founders of Opendoor, Figma, ClassPass, Clubhouse, Divvy, Gem, and Homebound.

The co-founders are proven leaders from the early team at proptech company Opendoor ($15B+ exit) and have each separately built and scaled products that today do $1B+ annual revenue combined.

We’re looking for the world’s top builders, executors, and believers to join us on this ride. You can learn more about us in Forbes and TechCrunch.

The Role

As the founding Data Scientist for Marketing Analytics, you will be the quantitative engine driving our member growth strategy. You will be the dedicated data partner to the Marketing team, responsible for everything from top-of-funnel channel analysis to understanding the long-term value of our members. This is a hybrid role that combines deep analytical insight with predictive modeling to help us grow our community efficiently and sustainably. You will be instrumental in building our marketing data foundations from the ground up.

What You'll Do

• Analyze Marketing Performance: Design and build core dashboards to monitor key performance indicators across all marketing channels.
• Drive Strategy with Insights: Conduct deep-dive analyses to understand channel effectiveness, measure campaign ROI, and identify opportunities for growth and optimization.
• Own Marketing Experimentation: Design, execute, and analyze incrementality tests and marketing experiments to determine the causal impact of new strategies, channels, and creative campaigns.
• Develop Predictive Models: Build foundational marketing science models, such as member LTV prediction, marketing attribution models, and lead scoring to improve efficiency.
• Partner Cross-Functionally: Collaborate closely with leaders in Marketing, Product, and Engineering to translate data-driven insights into actionable business strategies.
• Communicate Effectively: Present your findings and recommendations clearly to a variety of audiences, from marketing channel managers to the executive team.

What We're Looking For

Experience

• 5-7+ years of experience in a quantitative role such as marketing analytics, data science, or business intelligence, preferably within a consumer tech or marketplace company.

Technical Skills

• Expert-level proficiency in SQL.
• Programming skills in Python or R for statistical analysis and modeling.
• Experience with a BI tool such as Mode, Metabase, or Looker for building dashboards and communicating results.
• Familiarity with modern data warehouses is a plus.

Analytical Skills

• A deep understanding of quasi-experimental design and causal inference.
• Proven experience building and analyzing marketing funnels, CAC, LTV, and ROAS.
• Experience with predictive modeling techniques (e.g., regression, classification).

Business Acumen

• You are a strategic thinker who is passionate about understanding the "why" behind the data.
• You have a strong ability to translate complex data into actionable insights for non-technical stakeholders.
• You are a proactive, self-starting individual who is comfortable with ambiguity and excited to build things from scratch in a fast-paced environment.

Our Benefits

At Kindred, we know that good things happen when we look out for one another. We offer our employees the following benefits:

• Note: The opening spans more than one career level. The base salary offered depends on many factors, such as work experience.