ReHaus is a data led e-commerce company looking to transform the vintage furniture sector. Working with the management team, you will be using your data engineering, machine learning and deep dive analytical skills to gather, cleanse and build usable datasets from a wide variety of raw data sources. As the first fulltime hire in the data team you will shape strategy for data usage within the business and your output will shape the future direction of the company.
About us
Backed by seasoned marketplace investors, ReHaus sells pre-owned designer furniture online. We operate with the belief everyone should have access to great design. Our mission is to create an online destination that redefines how consumers buy (and sell) pre-owned designer furniture.
About the Role
With a vast and varied remit, you will develop predictive models to forecast future demand. Using market and customer data to provide actionable insights you will improve sourcing, merchandising, pricing, customer acquisition and operational decision making. Working on new ways to make the most of the data, you will produce dashboards and present your findings to senior management.
About you
As the first full time hire in the data team, we're looking for a proactive, confident individual who is going to promote best practices, and wants to take the business forward in terms of the information you can get from data, and how it can be used to influence business decisions. We will expect you to get stuck in and be doing a bit of everything from the data engineering and data cleansing to the predictive modelling and analysis. As such, we are looking for someone with:
About us
Backed by seasoned marketplace investors, ReHaus sells pre-owned designer furniture online. We operate with the belief everyone should have access to great design. Our mission is to create an online destination that redefines how consumers buy (and sell) pre-owned designer furniture.
About the Role
With a vast and varied remit, you will develop predictive models to forecast future demand. Using market and customer data to provide actionable insights you will improve sourcing, merchandising, pricing, customer acquisition and operational decision making. Working on new ways to make the most of the data, you will produce dashboards and present your findings to senior management.
About you
As the first full time hire in the data team, we're looking for a proactive, confident individual who is going to promote best practices, and wants to take the business forward in terms of the information you can get from data, and how it can be used to influence business decisions. We will expect you to get stuck in and be doing a bit of everything from the data engineering and data cleansing to the predictive modelling and analysis. As such, we are looking for someone with:
- Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
- At least 3 years' of experience in quantitative analytics or data modelling in a commercial environment (ideally retail, digital, marketing or e-commerce)
- Deep understanding of predictive modelling, machine-learning, clustering and classification techniques, and algorithms
- Knowledge of Machine Learning Techniques and evidence of personally amending existing frameworks to suit the exact nature of the task at hand
- Demonstrable experience of utilising data science techniques / predictive analytics to drive better decisions within a commercial environment that contribute to sustainable growth
- Highly analytical and metrics-driven with an ability to interpret data and use to drive strategic business decisions
Nice to haves:
- Always curious and willing to learn new skills
- A problem solver with a deep analytical mindset
- Ability to think creatively and insightfully about business problems
- A critical thinker with very strong attention to detail
- Awareness of digital marketing and factors that influence online customer acquisition
We offer:
- £50,000 salary + equity
- 25 days' holiday + bank holidays per year
- a low bureaucracy environment
- flexible working
Location
We’re (usually!) based in a lovely office in Clerkenwell. Since COVID-19 struck, we switched to working from home. Our plans are to continue working from home until at least mid 2021 when we expect to mix home and office work.
Employment Type
Full-time