Data Scientist

What we do at Codat

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 a Data Scientist to capitalize on our rapidly growing data infrastructure to provide advanced analytics and develop models designed to increase growth and efficiency. There is an immense amount of opportunity to leverage data in more sophisticated ways across Codat’s different functions like Product, Engineering, Sales and Marketing. The role will also entail a high degree of autonomy, responsibility, and exposure to senior stakeholders across the business. It is reasonable to expect some data engineering-style work such as writing SQL to pre-process data.

Key responsibilities:

  • Be a critical member of a tight-knit and high-performing Data and Analytics team
  • Lead on Codat’s internal data science efforts, specifically:
    • Identify metrics of interest to the business
    • Design and productionise predictive models for key metrics
    • Work cross-functionally to implement solutions that translate analytical insight into real value-add data-driven action
  • Contribute to Codat’s data engineering strategy, and be responsible for the maintenance of key analytical data sources
  • Prioritize 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

Our values

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 data science environment at a start-up or scale-up
  • 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
  • Technical skills: Python, SQL, Data science with some experience working with commercial data in a time-series environment
  • Experience translating predictive models into real value-add action, in addition to expertise in data science and predictive modeling
  • Data Science or quantitative skills learned either through an academic qualification or professional experience
  • Drive, enthusiasm, intellectual curiosity, willingness to learn
  • Experience working with commercial data i.e. data from different parts of a business
  • Software familiarity: Microsoft Azure, Pyspark / Databricks, dbt, Looker, Snowflake

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