Hi, we’re Bloom & Wild. We don’t just send flowers. We help our customers to care wildly. Caring wildly is celebrating the little things we all do for each other every day. Not just the big occasions. It’s being there for the highs. Stepping up for the lows.
We care wildly about people and our planet. Which is why we’re so proud to be a certified B Corp™ – committed to making long-term positive change for our community, and the world around us.
Founded in 2013, our mission back then was to make sending and receiving flowers the joy that it should be, by harnessing technology, brand and letterbox delivery. We announced £75 million Series D funding in 2021 and that same year acquired bloomon in The Netherlands and Bergamotte in France. Together, we’ve fulfilled and delivered over 20 million orders (and counting!), making us the largest direct to consumer flower business in Europe.
Now home to a family of 3 beautiful brands, we’re driven by our vision to create the destination for making life a little more thoughtful and beautiful. And we won't stop at flowers and plants. Starting with the Bloom & Wild brand, we're expanding our gifting offering to other categories like cakes, candles and cocktails. This is all part of our ambition to build Europe's #1 direct to consumer gifting destination.
⚙️Data Science at Bloom & Wild
You will be joining a small data science team, currently consisting of 3 data scientists within an overall Bloom & Wild team of over 350 people and growing! We are a small, driven team that are set on expanding usage of data science across Bloom & Wild. We collaborate closely with the data engineering and product teams, the rest of the technology team, a separate business intelligence and analytics team, our CRM and operations teams to help us identify areas of opportunities and bring our projects to life.
With millions of customers and hundreds of thousands of monthly transactions, we have a large and growing dataset that we use for training machine learning models. We have a number of models in production, from recommendation to forecasting engines, and a backlog of ideas to brainstorm, prototype and test.
In terms of technologies: Python, Snowflake, dbt, git, ECS, Lambdas and Airflow on AWS are part of our day to day. We welcome applications from candidates based within roughly two hours of the UK time zone, covering many European countries. This helps us stay aligned as a team while supporting flexible, remote-friendly ways of working. At Bloom & Wild, squads meet in person at least once per quarter in order to maintain connections, collaborate on larger projects and have fun together.
Most of our team is based in the UK or The Netherlands and works in a flexible model, with choice in how often they travel to the office. Our squads meet in person at least once per quarter in order to maintain connections, collaborate on larger projects and have fun together. We welcome applications from candidates based remotely within roughly two hours of the UK time zone, covering many European countries. This helps us stay aligned as a team while supporting flexible, remote-friendly ways of working.
🚨Please note🚨
We’re excited to open applications for this role ahead of the new year. While you’re welcome to submit your application now, we want to be transparent that our recruitment process will begin in early January. As a people-first business, we also want to recognise that this may mean a short delay before you hear from us. Thank you for your patience and understanding—your application genuinely matters to us, and we look forward to reconnecting in the new year.
💻 What you’ll be doing
On a typical day for the data science team, we sync in the morning during stand-ups to discuss the on-going work and identify blockers or areas of collaboration. During the day, we will be brainstorming and prototyping models to solve specific business problems. Or, we will be writing robust, well-tested code for new model deployments or supporting the design of A/B tests. Or we can be collaborating with other teams to gain a better understanding of business domain, data or requirements
