Senior Data Scientist, Growth

fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

As a Senior Data Scientist for Growth at fal, you won't be inheriting a mature growth analytics stack — you'll be building one. Our marketing function is early: we're just beginning to stand up performance marketing, hiring our first dedicated marketers, and establishing the foundational taxonomy, instrumentation, and measurement frameworks that will power our growth for years to come.

You'll be the analytical co-founder of our growth motion, working alongside marketing leadership and company leadership to define how we measure, evaluate, and scale fal's acquisition from the ground up. If you've ever wished you could design a company's growth analytics layer before the bad habits set in, this is that role.

• →Build fal's growth measurement foundation — define the event taxonomy, attribution model, channel hierarchy, and reporting infrastructure that the entire marketing org will run on.
• →Stand up acquisition analytics across paid, organic, content, community, and partnership channels, starting from early-stage instrumentation and working toward a unified view of channel performance.
• →Shape our top-of-funnel growth strategy alongside marketing and leadership; translate early signals from nascent channels into clear recommendations on where to double down, where to experiment, and where to wait.
• →Define and operationalize the unit economics of fal's growth motion (CAC, LTV, LTV:CAC, payback period, ROAS, and cohort performance by channel).
• →Design and run growth experiments end-to-end: shape the hypothesis, build the measurement plan, analyze the results, and turn findings into the next round of bets.
• →Help shape the broader data and analytics capability supporting growth as the team scales.

• 5+ years of experience in data science, growth analytics, or growth strategy, ideally at PLG or developer-tools companies with a commercial motion.
• Experience building growth analytics infrastructure from early stages — you've defined the taxonomy, stood up the pipelines and dealt with the messy reality of instrumenting a product that wasn't built with measurement in mind.
• A strategy-and-tactics mindset — you don't just measure growth, you recommend what to do next and see those recommendations through.
• Hands-on experience with channel-level acquisition analysis across paid (Google, Meta), organic, content, community, and partnerships, including the judgment to evaluate channels with limited data.
• Strong fluency with growth unit economics — CAC, LTV, LTV:CAC, payback period, ROAS, attribution, and incrementality.
• Experience building LTV and cohort models, including in environments where the data is sparse or the product is evolving quickly.
• Advanced SQL and proficiency in Python for analytics and experimentation.
• Strong experimentation chops: A/B testing, holdout designs, causal inference and the pragmatism to know when a quick read is better than a perfect test.
• Comfort with ambiguity and an owner mentality.
• A track record of shipping growth experiments and recommendations that changed how a marketing budget got spent.

• Experience standing up performance marketing measurement for a team scaling from zero to meaningful ad spend.
• Experience working on developer-facing or API products.
• Background in community-led, content-led, or partnerships-led growth motions.
• Early-stage or fast-scaling environment experience, especially as a first or early data hire supporting marketing.