Moneybox is the award-winning app that helps you turn your money into something greater. We’ve brought saving, investing, home-buying, and retirement services all together into one simple app, so it’s easier than ever to achieve your goals and build wealth, whatever your starting point.
Moneybox has embarked on an exciting journey to use statistical thinking and machine learning to improve making decisions with data – using the
foundational data models and pipelines setup by the Insight team to solve the most strategic challenges Moneybox has on a medium to long horizon.
As a data scientist in Moneybox you will be working with insight analysts to operationalize and standardise a system of metrics that serve as good foundations for understanding the causal mechanics of Moneybox as a business. You will be working on supporting experimentation efforts of analysts to ensure they have the appropriate tooling to infer causal relationships from the data and the changes being made on the product.
With a good understanding of causal mechanics – you’ll work with the Senior Data Scientist and Head of Decision Science to build modelling capability to solve immediate user and business problems and to help personalise the experience of Moneybox so that it’s deeply relevant and relatable at a local level, with the eventual goal of driving fully-fledged AI solutions.
Our current data platform is Databricks, with the tables being populated using dbt processes setup by our partners in the Insight organisation – and you’d be expected to use Databricks in your day-to-day job which we’ll cover in your onboarding.
What you’ll do
You will be responsible for increasing the rigour of decision-making being done with data – either at stakeholder level or through automated decisioning:
- Research salient metrics that explain components of our business architecture
- Quantify and systematise causal relationships from various product levers to drive user outcomes and business goals
- Build modelling capacity to infer data points needed to solve user and business goals
- Optimise the user experience by building modelling capacity that can inform automated decision-making
- Build internal tooling to support better decision-making with data through experimentation and analysis
Who you are
- Have experience in using Python or R to examine large datasets through distributed compute and produce impactful analysis and solutions
- Have a scientific mindset that always questions the validity of data when making conclusions and informing decisions
- Love to drive the business by providing blueprints for how data can be used to inform business strategy and product strategy
- Thrive in a fast-paced startup environment
- Eager to learn new things and challenge your existing frameworks
- Thrive in ambiguity and help drive clarity through salient analysis and solutions, even when presented with fuzzy business problems
- You know the difference between perfect and good – and can optimise your workflows to discount hypotheses quickly where appropriate and go deep when needed
Experience and skills – essential!
- 1+ years of industry experience in driving product impact through data science analysis and solutions OR PhD in a field using quantitative analysis to drive scientific decision-making and 3+ years of academic research experience
- Expertise in using Python OR R to investigate large datasets
- Experience in using parallelism and distributed compute to deal with scale of large datasets – Spark experience is preferred, but not essential
- Advanced knowledge of SQL
- High degree of knowledge of applied statistics
- Demonstrated ability to use statistical analysis to increase fidelity of conclusions
- Knowledge of feature engineering and how to transform data to optimise for more signal towards a given objective
- Demonstrated ability to use advanced and custom visualisation to help explain complex relationships and patterns
Experience and skills – not essential for the role but desirable
- Demonstrated track record of productionising data products to deliver repeated value to stakeholders – be it models or interactive analysis solutions
- Knowledge of machine learning algorithms and how they can be employed to optimise the user experience
- Knowledge of using Bayesian frameworks for experiment analysis and inference
- Experience in using Databricks or a similar platform for analysis.
What’s in it for you?
- Opportunity to join a fast-growing, award-winning and super ambitious business.
- Work with a friendly team of highly motivated individuals.
- Be in an environment where you are listened to and can actually have an impact.
- Thriving collaborative and inclusive company culture.
- Competitive remuneration package.
- Company shares
- Company pension scheme
- Hybrid working environment
- Home office furniture allowance
- Personal Annual Learning and Development budget
- Private Medical Insurance
- Health Cash Plan (cashback on visits to the dentist & opticians etc)
- Cycle to work scheme
- Gympass subscription to a variety of gyms and wellbeing apps
- Enhanced parental pay & leave
- 25 days holiday + bank holidays with additional days added with length of service.
Our office is in London, by the Oxo Tower