Staff Data Analyst, Marketplace Insights

Food has lost its soul to modern convenience. And with it, it has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 50 million meals a year from the industry’s best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul.

Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world.

If that mission has you hungry in more ways than one, you’ve found the right job posting.

Data Analysts are the people who form a marriage of minds with product, marketing and commercial managers and provide them the insights they need to drive improvements in their products. They explore data, create impactful visualizations and visualization and design and analyze experiments to fuel team learning and innovation. Over time, as both the learning needs and the analysts' understanding of how to address them mature, they build their understanding into self-service insights dashboards that enable learnings to be generated without the direct support of data professionals. This creates the opportunity to go deeper on other areas. It’s a role where mastery in metric setting, visualization, data storytelling, experimentation and partnering come together to facilitate team measurement and learningwithin their daily rhythms.

• →Transform our understanding of how users discover and order food through behavioral insights: Collaborate with Marketplace and Menu teams to understand user behaviors and drivers behind their interactions with our platform. Uncover patterns and trends in menu discovery, evaluation and ordering actions, informing the improvement of the marketplace experience. Success will be measured by the number of insights that have led to improvements in user experience and engagement metrics, resulting in increased customer satisfaction and retention.
• →Enable self-service insights where you can: Develop intuitive, interactive data visualizations in Tableau that empower stakeholders to easily explore and understand key metrics and trends. Create storytelling narratives within the dashboard that guide users through the data, enabling them to derive actionable insights independently. Success will be measured by the adoption of the dashboard among stakeholders and the frequency of use in decision-making processes, indicating improved data literacy.
• →Define metrics and customer segments to gain further insights: Define relevant metric frameworks (behavioral and performance) and user segmentations that align to the learning goals of the team. Work with the product teams to prove your segmentations can be used to build more personalized customer experience. Success will be measured by the change in metrics as a result of improved feature targeting, prioritization and personalization.
• →Help with the product teams scale up early testing and controlled experiments: Design, support execution of and analyze (semi-)controlled experiments. Leverage platforms to enable self-serve conclusions about success, but provide hands on support to understand in-test behaviors. Produce learnings and work closely with user experience researchers to help the product teams understand the why of their successes and failures. Success will be measured by the number of major product features where roll out and full development is evidenced through early testing and light touch experimentation.
• →Map and clearly articulate our learning needs: Work with Product, User Research, and UX teams to understand the user and commercial challenges in their product area, converting into clearly articulated learning goals and roadmaps. Proactively identify new unknown learning needs that can inform product direction and improve the user experience. Success will be measured by the number of product iterations and innovations that successfully move the product team's success metrics, as a result of your insights.
• →Drive data creation to maximize observability of user behaviors in the marketplace: Collaborate with engineering teams to implement robust data collection strategies, ensuring comprehensive tracking of marketplace interactions and behaviors. Define target schemas and work with engineers to implement common schemas design principles and conventions as needed to maintain data quality and integrity at source. Success will be achieved by ensuring complete and accurate data collection, enabling a clear understanding of Marketplace performance through well-defined and reliable data sources.
• →Be a multiplier for other analysts in the team: Help the mid and senior engineers in the team make stretch improvements in their already strong code quality and analytical problem solving. Be the strongest insights producer in the team and the data vizard that everyone looks to for tips on how to improve their own analytics practices. Success will be measured by both the observable growth in the team (e.g. more impactful insights, more self-service insights enabled) and the direct feedback you get from them about the positive impact you’re having on their practices.

• High autonomy in partnering with non technical stakeholders
• HIgh autonomy in executing to produce insights with data (e.g. SQL, Tableau, Python, dbt)
• High agency and growth mindset

• 7-10 years in similar analyst roles, with a pattern of high achievement.