Data Scientist

We're looking for a Staff Data Scientist to help define the company's growth strategy as users increasingly discover and adopt software through LLM interfaces like ChatGPT, Claude, and Gemini. With millions of knowledge workers now starting their workday in conversational AI tools, we're at an inflection point in how productivity software reaches users. You'll drive the company's acquisition playbook for the emerging LLM-driven channels and re-imagine new customer onboarding in the AI-era.

As part of the PLG organization, you'll leverage data to influence how new users discover, learn about, and decide to start using and paying for the company.

The company's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value. Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling.

This role is based in our Vancouver office with an office‑centric hybrid schedule. The standard in‑office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you’re interviewing for this role, your recruiter will share more about the in‑office requirements.

• Work closely with Product Managers and User Researchers (UXR) to understand the needs of our new customers in their first few minutes of interaction with the company, employing data frameworks and methodologies to understand our user segments, visualize the new user funnel, identify levers for driving conversion revenue, and personalize the onboarding journey to ensure better adoption outcomes.
• Act as the “Data Lead” in a triad with Product and Engineering stakeholders to identify multi‑year growth opportunities and prioritize the roadmap.
• Design experiments that measure product progress, and own key performance metrics.
• Collaborate and mentor fellow Data Scientists in the team to research, identify and disseminate best practices across teams.
• Work in a high-performance, dynamic team with a strong focus on velocity and software quality and learn about the upcoming field of AI‑Optimization and how LLMs can help boost the company’s value proposition.

• 5–7 years of data science experience, with majority in growth-focused roles at B2B SaaS companies
• Proven track record driving acquisition and activation for B2B SaaS products, with specific experience in top-of-funnel growth and new user acquisition.
• 0→1 builder mentality. You’ve demonstrated the ability to thrive in highly ambiguous environments where you’re inventing new playbooks rather than executing existing ones. You’re energized by pioneering work.
• Experience with AI/ML products, LLM APIs, or third-party platform integrations. Strong preference for candidates who’ve worked with conversational AI or built features integrating ChatGPT, Claude, or similar platforms.
• Strong analytical foundation with deep fluency in experimentation, A/B testing, and funnel optimization.
• Exceptional cross‑functional leadership. You write crisply, tell clear stories, and can influence across product, engineering, design, partnerships, sales, and executive stakeholders. You bring clarity to ambiguity.
• Strategic business acumen to balance user experience with revenue objectives while translating emerging technology trends into actionable product strategy.
• Genuine AI enthusiasm. You’re curious, adaptable, and genuinely excited about how LLMs are transforming software discovery and adoption.
• Expert in relational data modeling and SQL and fluent in at least one modern language useful for data processing (e.g. R, Python, or Scala).
• Familiarity with statistical methods including experimental design, regression, causal inference with observational data and time‑series modeling.
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or…