Product Data Scientist
Founded in Zurich in 2010, Wheely currently operates in London, Moscow, and is launching in Paris later this year. Today, the brand has established itself as the go-to chauffeur-driven app - and is experiencing rapid growth.
We are the leader in the luxury ride-hailing market, employing over 100 people and working with 3000 chauffeurs. As the UK’s highest rated ride-hailing app, we have been featured in the Evening Standard Magazine, GQ, Business Insider, and Sphere.
We are currently looking for an enthusiastic, forward-thinking and results-driven product data scientist to join the Wheely analytics team (we are currently four people in this team across London and Moscow) and help us grow the business further. You will need to have good technical skills, business understanding, and be operative from day one. In addition, we are looking for people that challenge the status quo and always strive to improve our systems and processes. We are currently reshaping the analytics team at Wheely so there is a lot of opportunities to contribute to help building a team and improving overall processes.
- Data Analysis:
- Ability to manipulate large data sets using SQL and Python efficiently.
- Be able to understand problems both from a business and a technical perspective.
- Deliver actionable insights to the various stakeholders in the business using various statistical methodologies (clustering, forecasting, causal inference, machine learning, etc). The team works across all areas including product, marketing, etc.
- Automate processes and analyses using dashboards.
- Collaborate with various stakeholders across the business in order to better understand how the analytics team can provide value to the business.
- Contribute to the development of knowledge within the team. There are many interesting areas to which you will contribute (e.g. manipulation of geospatial data, real-time data, advanced analysis techniques for segmentation/modelling/causal inference, etc)
- Contribute to the improvement of processes within the team.
- Data engineering:
- Please note that, although this role will focus on data analysis, there will be an opportunity to gain exposure to data engineering. We are a small team that currently takes care of the whole process (ETL to analysis).
- Understand how our overall pipeline works and have a working-level understanding of our various tools for ETL.
- 3+ years experience in a similar role, ideally in a data-heavy environment (e.g. tech/online industry, etc)
- Strong technical skills including SQL (analytic functions, performance tuning, etc) and Python (pandas, seaborn, scikit-learn, etc). The team uses those two languages on a daily basis and you will be expected to be proficient from day one.
- Strong business acumen. Beyond being able to manipulate data, you are able to understand whether or not solving a problem can generate value for the business overall.
- Good understanding of statistics. In other words you are comfortable discussing various techniques including statistical testing (both parametric and non parametric), modelling, etc.
- Ability to present complex problems in both simple and technical terms depending on the audience.
- Strong attention to detail and accountability.
- An inquisitive mind by nature. You always go the extra mile in order to understand ‘why’ things happen rather than only ‘what’ happens.
- A natural desire to change the status quo in order to improve systems and processes. We are always looking to improve.
- Experience with the manipulation and analysis of geospatial data is a plus but not necessary.
- Experience with version control tools (e.g. git) is a plus but not necessary.
- Experience with visualisation tools (e.g. Tableau, Looker) is a plus but not necessary.
- We offer a highly competitive compensation package, including bonuses
- The Wheely culture is one of equity for all, which means that you will be more than just an employee. You will be a co-owner
- Delicious lunches provided daily
- Monthly Wheely credit.