Since our launch in 2015 weve lent over 10bn to ambitious entrepreneurs up and down the UK. Thats led to the creation of over 40000 new jobs and over 29000 new homes and were not about to stop there. Were 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 dont want another cog in the machine were 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 Banks 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:
Design implement and evaluate macroeconomic forecasting models time series regressions and machine learning models (including basic neural nets like RNN LSTM architecture).
Apply and explain statistical concepts like regression correlation multicollinearity stationarity autocorrelation and model assumptions to non-technical teams.
Work with time series panel and structured tabular data and perform feature engineering data cleaning and model validation.
Work with SQL to extract and manipulate data perform preprocessing and feature engineering tune models.
Work closely with business stakeholders domain experts and data engineers to define problems and deliver insights. Present insights and model performance clearly to technical and non-technical stakeholders
Optionally experiment with deep learning or generative AI models for internal R&D use cases
Required Experience:
7-8 years experience in Statistics Machine Learning Time Series modeling and Python
Desired Skills:
Bachelors or Masters 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.
Experience with real-world tabular datasets and business problem-solving
Strong applied knowledge of:
Supervised learning (linear/logistic regression decision trees ensemble models)
Probability distributions statistical inference hypothesis testing
Time Series modeling
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:
Deep learning experience (e.g. PyTorch TensorFlow)
Familiarity with version control (Git) dockers and AWS.
Exposure to GenAI concepts or LLM APIs (OpenAI HuggingFace LangChain)
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 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.
Our Investors
OakNorthHoldings (the parent entity of OakNorth Bank plc and ONci) has an equity base of over $1.2bn our investors include:GIC SMBCToscafund Coltrane andSoftBanks Vision Fund as well as founders of highly successful scale businesses.
Our Customers
In addition toOakNorthsown bank in the UK the software is also being deployed by US banksincluding:Fifth Third PNC M&T Bank Huntington and Old National Bank.
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