- United Kingdom
- Date Posted
- Jan. 12, 2022
- Data Science
Our mission is to make life easier for the lifeblood of economies globally; small and medium-sized businesses. Codat is a universal API for consented business financial data, powering the next generation of products and services for this historically underserved market.
We have offices in London, New York, Sydney, and a San Francisco office will be opening soon. We are a privately held company and have recently closed our Series B, being funded by Index Ventures, Tiger Global, American Express, PayPal and a line-up of world-class angel investors.
We live by our values of being united as a single team, building a product that is useful to our clients and their customers alike, with a focus and urgency that makes us unstoppable.
What you will be doing
We are looking for Data Science Engineers to increase data coverage, provide advanced analytics and develop data models designed to increase growth and efficiency. Due to Codat’s rapid growth, the successful candidate will be expected to work across both traditional engineering and science disciplines, owning both data sources and deciding how best to translate them into business value. There is an immense amount of opportunity to leverage data in more sophisticated ways across Codat’s different functions such as Product, Engineering, Sales and Marketing. The role entails a high degree of autonomy, responsibility, and exposure to senior stakeholders across the business. There is an opportunity for specialisation as Data matures.
- Be a critical member of a tight-knit and high-performing Data and Analytics team
- Plan, build and maintain Codat’s internal data infrastructure
- Lead internal data science efforts within specific areas of the business
- Contribute to Codat’s data engineering strategy, and be responsible for the maintenance of key analytical data sources
- Prioritise the most critical needs of the business and deliver analytics to support those areas
- Act as a spokesperson for the Data and Analytics Team internally, while building wider understanding and appreciation of data resources within Codat
- Provide technical expertise and training on analytical best practices to the data and wider business teams
- Lead efforts to migrate decision-making away from ad-hoc processes to being fully-underpinned by intelligent data-driven models
No matter what we’re doing - whether we’re speaking to customers, partners or to each other - we live by our values.
We believe in delivering useful technology that solves real problems for real businesses. We have a real want to do the stuff that isn’t always “cool” but makes a difference.
We believe that the people in the best teams push and enable each other to excel. We’re united when we have each other’s backs - when something goes wrong, we don’t blame, we work together to fix it. We embrace differences of opinion to end up with better outcomes. We don’t let our egos win.
We believe that an unstoppable drive towards a single, clearly stated goal is the best way to build great things. We are biased towards action - we make informed decisions and then we act. There is no such thing as an impossible problem, just a great challenge to sink our teeth into.
What excites us
- Demonstrably strong technical skills, with a focus on Python and SQL
- Demonstrable experience working in a combination of data engineering / data science environments at a scale-up or larger institution
- Familiarity with key engineering concepts such as data warehousing and ETL/ELT processes
- Familiarity with key data science concepts, ideally supported by a combination of relevant degree, educational qualifications, and data science project experience
- Professional drive and intellectual curiosity
- Excellent communication skills and EQ
- Experience with delivering projects against tight deadlines while maintaining a balance between programmatic rigor, speed of execution, and long-term planning
- Experience in owning data pipelines and living the life of a business-critical data engineer
- Evidence of taking initiative to deliver business value beyond the traditional responsibilities of data engineering
- Data Science or quantitative skills learned either through an academic qualification or professional experience
- Drive, enthusiasm, intellectual curiosity, willingness to learn
- Software with familiarity: Salesforce, Microsoft Azure, Node, Fivetran, Pyspark / Databricks, dbt, Looker, Snowflak
- If you are excited about applying for this role but aren’t certain you meet 100% of the criteria, we’d still love to hear from you