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Smart Investment Advisory

Data Scientist

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Who we are:

We’re a pan-European digital wealth manager with 50,000 active investors (growing fast!) and over £1.2 billion invested on our platform. With 130+ people across 4 offices in Italy, Germany and the UK, we’re supported and funded by Poste Italiane, Cabot Square Capital and Allianz.

We started in 2011 in Milan with a simple vision - to help more people improve their financial well-being by making personal investing straightforward and accessible through technology. Fast forward a few years, and we’re known as one of the most innovative fintechs headquartered in the heart of London.


Our Core Values:

We’ve built our business on three Principles:

Relationships are our first asset
We’re one team, built on trust, honesty and transparency. We value our relationships above all else.

Trust drives success
We give each other the space to grow. We empower our employees to succeed, so they can make a real impact.

Our customers dream big, just like us
We see the bigger picture and we make sure our customers see it, too. We’re always focused on the best outcomes for our clients and for each other, no matter what the goal, or how big the dream.

What this means in practice:

At Moneyfarm, diversity is the foundation of our competitive advantage. We value our employees for who they are – their backgrounds, experiences, talents, knowledge and individual differences. This is what makes us better at what we do. To accommodate our different needs/commitments, we offer flexible working to all. Our individual impact and output is what counts most.


  • Investigate and analyze data to generate insights to support optimization of business performance and improvement of product development.
  • Coordinate with senior stakeholders and different functional teams to implement models and monitor outcome KPIs.
  • Use predictive modeling to optimize customer experiences, revenue generation, ad targeting and other business outcomes.
  • Develop processes and tools to monitor and analyze model performance and prediction accuracy.
  • Develop company A/B testing framework using statistically robust methodologies.
  • Develop new analytic approaches for profiling and segmenting customers to generate insights and inform decisions.
  • Communicate insights to non-technical stakeholders using data storytelling and visualisation tools.
  • Identify and assess new potential data sources or tools to further enhance data capabilities.
  • Adhoc support for data analysis and building reports.
  • Working with the wider data and tech team to support and maintain the data environment and warehousing.

Must have:

  • Insatiable curiosity to derive relevant insights from data
  • At least 4-5 years experience with a BSc in Computer Science, Engineering or Maths
  • Strong proficiency in data manipulation and modelling using both SQL and Python
  • Experience in a wide range of ML techniques and algorithms e.g. regression, random forest, neural networks, clustering
  • Ability to test for statistical validity and bias
  • Ability to identify trends and patterns in complex data sets and visualisation in Tableau
  • Excellent written and verbal communication with non technical stakeholders

Nice to have:

  • Experience of big data tools (EMR, spark)
  • Familiarity with AWS environment and services
  • Understanding of dimensional and relational database modelling
  • Experience with ETL design, implementation and maintenance
  • Understanding of continuous development and delivery, agile methodology.
London • Milan
Job type
Visa sponsorship
Not Available
Hiring contact

Moneyfarm at a glance

Smart Investment Advisory

Moneyfarm focuses on Financial Services, Investment Management, Technology, Finance Technology, and Advice. Their company has offices in London, Frankfurt, Milan, and Cagliari. They have a mid-size team that's between 51-200 employees. To date, Moneyfarm has raised $109.4M of funding; their latest round was closed on September 2019.

You can view their website at http://www.moneyfarm.com or find them on Twitter, Facebook, and LinkedIn.

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