AVP - Data Science

Key Skills

Cloud computing, Python Programming, R Programming, SQL

Job Description

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.

AVP - Data Science will develop Statistical Models using statistical techniques including time series analysis, multivariate regression, test of significance etc.

This will help us to analyze large financial/market/high-frequency data sets and provide business performance conclusions for companies across multiple sectors e.g. linking macroeconomic data with specific sector performance, linking cost with revenue performance.

Job Responsibilities

Develop statistical models to analyze large financial/market/high-frequency data sets and provide business performance conclusions for companies across multiple sectors e.g. linking macroeconomic data with specific sector performance, linking cost with revenue performance

• Hands on experience of using R or Python with focus on statistical packages and working with databases such as SQL
• Extensively use statistical techniques including time series analysis, multivariate regression, test of significance etc. in building the models
• Deep knowledge of data science techniques such as linear/non-linear regression, maximum likelihood estimation, time series estimation & forecasting, optimization, simulations (Monte Carlo), asset pricing, data mining, pattern recognition, dimension reduction (PCA), Nowcasting and MIDAS
• Demonstrate strong understanding of key dynamics that explain sector performance and ability to independently verify the model outcomes
• Keep abreast of latest developments across sectors including impact of regulatory changes, impact of technological changes, structural changes in demand / supply environment etc.
• Extract information directly from multiple sources using web scraping and other techniques

Desired Skills

• Masters in Statistics / Economics / Business or equivalent with at least 4-7 years’ experience in the field of data science and statistical modeling
• Adeptness at linking statistical outcomes with business problems / situations and not thinking in silos of subject matter
• Ability to think critically in understanding client problem and brainstorm solution with colleagues of varied background (credit, market research, and technology)

SHORTDESCRIPTION

You will develop Statistical Models using statistical techniques including time series analysis, multivariate regression, test of significance etc. This will help us to analyze large financial/market/high-frequency data sets and provide business performance conclusions for companies across multiple sectors e.g. linking macroeconomic data with specific sector performance, linking cost with revenue performance.