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Data Analyst / Scientist (Remote OK) at Koia

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  • London
  • fulltime

About Koia

Koia is a venture backed FinTech startup looking to change the world of alternative assets. Via our mobile app, we enable anyone to easily invest in alternative assets at the click of a button. 

We believe in opening up opportunities, from assets to education. The world’s wealthiest have invested in assets such as fine wine, art and watches for hundreds of years. The same opportunities have remained out of reach to most people. We plan to change that.

Koia is bringing passion, excitement and a human touch to today’s faceless world of investing. We’re making investing engaging and community is at the core of what we do.

We are a diverse founding team and will consider applicants from all backgrounds.

 

Role Overview

We are looking for an experienced Data Analyst / Scientist* who’s excited about applying their skills to the fragmented world of alternatives. As one of our first hires, you will become an integral senior team member working directly with the founders at this exciting stage in Koia’s journey. 

The role will be ‘remote first’, however, there will be opportunities to work in person either in London, UK or Tallinn, Estonia.

*Title, compensation and exact job scope dependent on experience

Primary responsibilities:

You will be on a mission to supercharge our data offering from sourcing to visualisation, both internally and for our end users. We expect you to establish data analysis/science ‘best practice’ and define the roadmap for the team. You will work across a variety of projects both internally and externally. For example, developing predictive pricing models for new and emerging asset classes with unstructured and imperfect data sets and collaborating with the founders to identify issues and use data to propose solutions for effective decision making. As the team’s first data hire, you’ll initially also drive general business, product and marketing analytics. Think of building dashboards to show user activity, cohorts and revenues. You will be able to interpret and present complex data in a simple and intuitive way.

What you’ll bring to the role:

As an experienced data analyst, you will work collaboratively with our expanding engineering team as well as other stakeholders within the business. You will be well versed in mining, interrogating, managing and visualising data to provide unique insights. 

 

Essential:

  • Desire to work in an innovative FinTech startup with a passion for our mission at Koia
  • 3+ year of relevant Data Analysis experience 
  • Excellent analytical and problem-solving skills, with the ability to work with both structured and highly unstructured data sets
  • Experience with Python, Pandas, PyTorch, TensorFlow etc
  • Experience in database interrogation and analysis tools, such as Hadoop, SQL and SAS
  • Experience with cloud infrastructure and DevOps
  • Proven ability to research, develop, and test supervised and unsupervised learning models
  • Strong team working skills and a collaborative approach to working, sharing ideas and finding solutions
  • Willing to iterate, learn and stay flexible in a fast-moving and intense environment
  • Ability to speak and write in English fluently 

 

Nice to have, but not essential:

  • Experience within a FinTech or startup environment
  • Experience with data visualisation tools such as Tableau or Looker 
  • Passionate about alternative assets, collectibles or investing generally 
  • Degree/Masters/PhD in Applied Mathematics, Statistics, Economics, Engineering, Computer Science, etc. 
  • Understanding or experience with common tech stacks e.g. Flask, MongoDB, CDK, CI/CD, Github 
  • Decentralised finance (DeFi) / Blockchain experience 
  • Experience working within a regulated business 

 

Why join us?

  • Join as one of our first hires working directly with the founding team at a VC backed startup
  • Ability to work remotely with flexible hours 
  • Competitive compensation arrangement 
  • Significant career progression opportunities

 

Compensation / Options 

  • To be discussed, based on experience 
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