Data Science Analyst

Job Title – Data Science AssociateSince our launch in 2015, we’ve lent over £10bn to ambitious entrepreneurs up and down the UK. That’s led to the creation of over 40,000 new jobs and over 29,000 new homes – and we’re not about to stop there. We’re dedicated to helping trailblazing businesses thrive and our Debt Finance team are the drivers of our growth.This is a fantastic opportunity to join a fast-paced, growing bank with a reputation for doing things differently. We don’t want another cog in the machine, we’re looking for self-starters and bold thinkers who want to pave their own career paths.In a nutshell, the mission of the interns will join one of the Bank’s Credit (lending) teams and will analyze financial statements, including key lending and credit risk metrics.Are you ready to step up to the challenge?

Responsibilities:

• Build Forecasting & ML Models: Develop and evaluate macroeconomic forecasting models, time series regressions, and machine learning models (including basic neural nets like RNN, LSTM architecture).
• Statistical & Data Analysis: Apply and explain statistical concepts like regression, correlation, multicollinearity, stationarity, autocorrelation, and model assumptions to non-technical teams.
• Data Engineering: Work with SQL to extract and manipulate data, perform preprocessing and feature engineering, tune models.
• Cross-Functional Collaboration: Work closely with business stakeholders, domain experts, and data engineers to define problems and deliver insights.
• 2-3 years' experience in Statistics, Machine Learning, Time Series modeling, and Python

Desired Skills:

• Bachelor’s or Master’s in Statistics, Economics, Data Science, Computer Science, or a related field.
• Strong command over Python (pandas, NumPy, scikit-learn, statsmodels) and SQL for data analysis, modeling, and manipulation.
• Solid understanding of regression, time series forecasting, model diagnostics, and statistical tests (e.g., ADF, autocorrelation, VIF, R², RMSE)
• Experience with classical ML models and familiarity with basic deep learning architectures like LSTM or RNN.
• Comfortable working with small datasets where feature engineering and domain understanding matter most.
• Ability to explain complex concepts in simple terms and work effectively with both technical and non-technical stakeholders.
• Nice to have skills:
• Familiarity with version control (Git), dockers and AWS.
• Hands-on experience or foundational knowledge of LLMs, GPT-based agents, and Retrieval-Augmented Generation (RAG) workflows.

About OakNorth

• Small and medium-size enterprises (SME) are one of the biggest drivers of growth and innovation in economies all over the world. Despite these companies being a powerful force in the economy, many SMEs find it difficult to raise capital during critical stages of their company growth. Traditional commercial lending is optimised to make loans that are either too small to be effective or too large and expensive to be practical. At OakNorth, our mission is to help lenders fill this gap which we refer to as the “Missing Middle.” We are building a SaaS platform called the Credit Intelligence Suite which transforms commercial lending by helping banks build deeper relationships with their clients, open new, more profitable opportunities, whilst delivering credit decisions up to ten times faster than traditional models, with lower risk and greater efficiency.