Lenkie Inc.
Lenkie is a fast-growing UK SME lender on a mission to give small businesses access to fair, fast, and flexible finance. We're at an exciting inflection point - scaling our lending book and building the data infrastructure that will power our credit decisions for years to come. This is a rare opportunity to be the foundational data science hire and have a genuine hand in shaping how we think about credit risk, model development, and data-driven decisioning in risk as well as other parts of the business. About the job We're looking for a (Senior) Data Scientist with deep credit risk experience to join us as one of our earliest data hires. You'll work closely with the Head of Credit, Credit Risk Manager and CTO to build our modelling capability from the ground up - from scorecard development and underwriting automation to portfolio analytics and early warning systems as well as Customer Lifetime Values. This isn't a role where you'll plug into an existing machine. You'll be defining how we do things, building the infrastructure, and helping recruit the team around you as we grow. Key Responsibilities Build credit risk models - application scorecards, behavioural models, propensity models - across our SME lending products Create portfolio monitoring dashboards, MI packs, and early warning indicators for the credit and leadership teams Work with Open Banking, bureau, and alternative data sources to enrich our credit assessment Define data science best practices, tooling, and ways of working as the function grows Partner closely with Product, Engineering, and Credit to translate business problems into data solutions Support the Head of Credit and Credit Risk Manager on strategic projects - limit setting, pricing, risk appetite calibration Use your data science expertise for projects outside of credit risk, e.g. Customer Lifetime Value modeling. Qualifications/Required Skills 2-5 years of experience in data science or quantitative analysis, with a strong focus on credit risk in a fintech or lending environment Hands-on experience building credit scorecards or risk models (application, behavioural, or collections) Proficiency in Python and SQL; experience with ML frameworks (scikit-learn, XGBoost, etc.) Familiarity with Open Banking data, bureau data (Experian, Equifax, TransUnion), or alternative data sources Comfort working in small, fast-moving teams where you have to be both strategic and hands-on Experience with SME lending is a strong plus (vs. consumer) Strong communicator - able to explain model outputs and data insights to non-technical stakeholders How we reward performance Be a founding member of the data team with real ownership and influence Competitive salary + meaningful equity Hybrid working from our London office A mission you can get behind - helping small businesses access the finance they deserve We're building a diverse, inclusive and supportive team where everyone can do their best work. We welcome applications from people of all backgrounds, experiences and perspectives, and we do not discriminate based on age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation. If you require any reasonable adjustments during the recruitment process, please let us know.
Lenkie is a fast-growing UK SME lender on a mission to give small businesses access to fair, fast, and flexible finance. We're at an exciting inflection point - scaling our lending book and building the data infrastructure that will power our credit decisions for years to come. This is a rare opportunity to be the foundational data science hire and have a genuine hand in shaping how we think about credit risk, model development, and data-driven decisioning in risk as well as other parts of the business. About the job We're looking for a (Senior) Data Scientist with deep credit risk experience to join us as one of our earliest data hires. You'll work closely with the Head of Credit, Credit Risk Manager and CTO to build our modelling capability from the ground up - from scorecard development and underwriting automation to portfolio analytics and early warning systems as well as Customer Lifetime Values. This isn't a role where you'll plug into an existing machine. You'll be defining how we do things, building the infrastructure, and helping recruit the team around you as we grow. Key Responsibilities Build credit risk models - application scorecards, behavioural models, propensity models - across our SME lending products Create portfolio monitoring dashboards, MI packs, and early warning indicators for the credit and leadership teams Work with Open Banking, bureau, and alternative data sources to enrich our credit assessment Define data science best practices, tooling, and ways of working as the function grows Partner closely with Product, Engineering, and Credit to translate business problems into data solutions Support the Head of Credit and Credit Risk Manager on strategic projects - limit setting, pricing, risk appetite calibration Use your data science expertise for projects outside of credit risk, e.g. Customer Lifetime Value modeling. Qualifications/Required Skills 2-5 years of experience in data science or quantitative analysis, with a strong focus on credit risk in a fintech or lending environment Hands-on experience building credit scorecards or risk models (application, behavioural, or collections) Proficiency in Python and SQL; experience with ML frameworks (scikit-learn, XGBoost, etc.) Familiarity with Open Banking data, bureau data (Experian, Equifax, TransUnion), or alternative data sources Comfort working in small, fast-moving teams where you have to be both strategic and hands-on Experience with SME lending is a strong plus (vs. consumer) Strong communicator - able to explain model outputs and data insights to non-technical stakeholders How we reward performance Be a founding member of the data team with real ownership and influence Competitive salary + meaningful equity Hybrid working from our London office A mission you can get behind - helping small businesses access the finance they deserve We're building a diverse, inclusive and supportive team where everyone can do their best work. We welcome applications from people of all backgrounds, experiences and perspectives, and we do not discriminate based on age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation. If you require any reasonable adjustments during the recruitment process, please let us know.