Senior Data Scientist
✨ AI Summary
Join our mission-driven, fully remote team as a Senior Data Scientist! At Buffer, we provide innovative social media and brand-building tools for small businesses, creators, and individuals. Our goal is to empower small enterprises to thrive through exceptional support and inspiring content.
In this pivotal role, you will be instrumental in enhancing our data-driven decision-making for product and growth strategies. As the lead Data Scientist, you will collaborate with various teams to address critical inquiries, assess impacts, and identify new opportunities. Initially, your focus will be on fulfilling core analytical needs, with an eventual aim to streamline data processes and reduce ad-hoc dependencies.
Main Responsibilities:
- Provide analytical support to product and growth teams, influencing decision-making.
- Develop and maintain behavioral and business models related to customer engagement.
- Conduct in-depth analyses to discover product and growth opportunities.
- Design and interpret experiments, including A/B tests.
- Establish success metrics and evaluation frameworks in collaboration with cross-functional teams.
- Enhance Buffer's data systems and measurement approaches.
- Utilize AI tools to enhance accessibility and efficiency in data analysis.
How to Apply:
If you believe you're a great fit for this role, we want to hear from you! Submit your application and resume, detailing your interest in joining Buffer. Our hiring process includes interviews and a collaborative project to ensure mutual fit.
Requirements
- Significant experience as a Data Scientist (or equivalent) in a SaaS or product-led growth (PLG) environment, with a str
- Experience leveraging modern data and AI-assisted tools to increase analytical leverage, improve insight accessibility,
- High degree of ownership and judgment, comfortable acting as the primary or most senior Data Scientist within a small te
- Skilled at translating complex, messy data and ambiguous questions into clear metrics, narratives, and actionable insigh
- Experience building and maintaining analytical models across the full customer lifecycle, including acquisition, activat
- Strong foundation in statistical analysis and causal reasoning, with fluency in SQL and advanced experience using Python
- Deep hands-on experience with modern analytics stacks, including SQL-based data warehouses (BigQuery preferred; Snowflak
