Data Scientist

Who we are:

Nutmeg is Europe’s leading Digital Wealth Manager, but we don’t want to stop there. We’re continuing to build our platform to help us achieve our mission of being the most trusted Digital Wealth Manager in the world. In 2021 Nutmeg became a J.P.Morgan company offering investments and digital wealth management services to consumers, complementing Chase’s digital bank in the UK.

Since being founded we've:

• Grown to 180+ employees
• Launched 4 amazing products including JISA and Lifetime ISA
• Won multiple awards including Best Online Stocks & Shares ISA Provider for the fifth year in a row!

We hit the 170,000 investor milestone in 2021 and now manage over £4 billion AUM.

*We offer flexible working*

Job in a nutshell:

This is a fantastic opportunity for a deep thinker with an analytical background to join and develop their career in a market leading FinTech company. The Data Scientist will be responsible for making sense of Nutmeg’s customer data through exploration and interrogation.

In this role you will be scoping, prioritizing and delivering analytics projects and applying statistical and data science skills to identify risks and opportunities for the business.

Your primary focus will be in applying state-of-the art data mining techniques, doing statistical analysis, and transforming our data into powerful business insights to impact Nutmeg’s KPIs.

It's a chance to be part of a multi-disciplinary team embedded in the product, where you'll collaborate with engineering, finance, product, and commercial teams to tackle some of the investment sector’s biggest problems while keeping aligned with the product’s vision and strategy, with a particular focus on personalisation and optimisation.

At Nutmeg, you will find a fast-paced environment where data science results are delivered at short iterations, where results are measurable and effective, and where credit is always given when due.

Requirements

Your skills:

• You are comfortable solving and productionizing supervised machine learning solutions.
• You are keen to deploy reinforcement learning solutions, such as bandit algorithms.
• Proficient in SQL and Python with working experience of scientific computing and machine learning libraries (NumPy, SciPy, Pandas, Matplotlib and Scikit-Learn). Willing to learn other languages where required, for example R.
• Intellectually curious, practical, and ready to learn and discover, you don’t just apply out-of-the-box models, you know how they work, when they work and why they work. You are a critical thinker.
• You’ll be the kind of person is comfortable working alone and as part of closely collaborative teams. You enjoy sharing your work and how you got there.
• Working experience with tools and frameworks such as Airflow, Docker, Rest APIs, Jenkins.
• You have experience of taking a project from raw data, through exploratory analysis and algorithmic development, to production and ongoing improvement.
• You are truly scientific: understanding of frequentist and Bayesian A/B testing.
• An entrepreneurial mind-set. Figuring out how to improve business processes and finding opportunities to apply data science techniques to real problems is as exciting to you as solving them.
• You’ll be comfortable taking complex ideas and communicating them to different audiences.
• MSc or PhD in a quantitative field such as Maths, Statistics, Operational Research or Computer Science.

You might also have:

• Working experience with common MLOps tools such as MLFlow and DCV and managed services such as AWS.
• Worked on real-time machine learning (online learning) solutions including bandit algorithms and their application in industry.
• Basic understanding of advanced statistical models such as Generalised Linear Models, Linear Mixed Effect Models, Survival Analysis.
• Experience with advanced experimental design.
• Familiar with object-oriented programming concepts.