Hybrid Data Scientist - ML & Analytics for FinTech Impact

Kroo Bank; Greater London; Hybrid; GBP 60,000 - 95,000; Full time

Benefits offered by this job

Hybrid working

London office

Job summary

Kroo Bank in London is seeking a Data Scientist to build, evaluate, and deploy data science solutions that inform strategic decisions and improve customer outcomes. You will work across product, risk, operations, compliance, and engineering to deploy robust models and analytics.

You will apply ML and statistical methods, design experiments, and ensure governance and reproducibility across production environments. Strong Python and SQL/dbt skills are essential for delivering impactful insights.

Qualifications

• Experience building and evaluating statistical and machine learning models in a commercial environment.
• Strong analytical and problem solving skills with the ability to translate business challenges into practical data science solutions.
• Ability to conduct data collection by independently sourcing and defining required datasets, partnering with stakeholders to clarify data needs and ensure appropriate coverage and traceability
• Ability to perform data cleaning effectively by independently applying robust cleaning approaches, proactively identifying data quality issues, and contributing to improving data reliability and standards
• Ability to conduct basic data analysis by independently performing exploratory analysis and statistical investigation, translating findings into clear insights and actionable recommendations
• Strong programming fundamentals with experience writing maintainable Python code for analysis and modelling, contributing to shared codebases through good practices, testing, and documentation
• Experience using SQL and dbt to extract, transform, validate, and analyse data
• Ability to apply visualisation techniques to produce clear, purposeful visualisations and model performance summaries that support decision making across technical and non technical audiences
• Ability to communicate effectively by explaining complex analytical concepts clearly and tailoring messages to a wide range of stakeholders
• Strong attention to detail, ensuring outputs are validated, reproducible, and documented in line with governance and compliance requirements
• Ability to manage data projects proficiently by planning and delivering work to agreed timelines, managing competing priorities, and contributing positively to team delivery processes
• Experience working collaboratively with Product, Risk, Operations, Compliance, and Engineering teams is beneficial
• Awareness of model governance, risk management, and regulatory considerations within a financial services environment is advantageous

Responsibilities

• Build and iterate on statistical and machine learning models to solve business problems across areas such as credit risk, fraud, customer engagement, and operational efficiency
• Partner with stakeholders to define problem statements, success metrics, data requirements, and practical implementation plans
• Conduct data exploration and feature engineering to uncover drivers of outcomes and improve model performance and interpretability
• Develop robust evaluation frameworks, including appropriate baselines, validation strategies, monitoring metrics, and model performance reporting
• Support deployment of models into production in collaboration with Engineering, contributing to reproducible pipelines and model documentation
• Monitor models in production, identify performance drift, propose improvements, and support ongoing recalibration or retraining where required
• Apply probability and statistical inference to design experiments, interpret results, and provide clear recommendations to stakeholders
• Contribute to high quality data practices by identifying data quality issues, supporting cleaning and normalisation approaches, and defining standards for reliable datasets
• Write maintainable, well tested Python code using common data science libraries, and follow engineering best practices appropriate for production systems
• Use SQL and dbt to extract, transform, and validate data for analysis and modelling, ensuring traceability and reliability of outputs
• Collaborate with Risk, Compliance, and Audit stakeholders to ensure data science work is appropriately governed, documented, and aligned with regulatory expectations
• Support continuous improvement across data science methodologies, tooling, and ways of working

Skills

Modeling

Analytical thinking

Data sourcing

Data cleaning

Exploratory data analysis

Python

SQL

dbt

Data visualization

Communication

Attention to detail

Project management

Cross-functional collaboration

Governance

Tools

Python

SQL

dbt

Job description

Kroo Bank in London is seeking a Data Scientist to build, evaluate, and deploy data science solutions that inform strategic decisions and improve customer outcomes. You will work across product, risk, operations, compliance, and engineering to deploy robust models and analytics.

You will apply ML and statistical methods, design experiments, and ensure governance and reproducibility across production environments. Strong Python and SQL/dbt skills are essential for delivering impactful insights.