Kroo Ltd. logo
Kroo Ltd.

Kroo Ltd. is a United Kingdom-based financial services company that is striving to provide a platform “where friends and money meet.” The company, as an emp

Data Scientist

Location

United Kingdom

Posted

2 days ago

Salary

0

Seniority

Senior

Job Description

Data Scientist

Kroo Ltd.

Title: Data Scientist Location: London England GB Job Description: Hybrid Technology Full time London, England, United Kingdom OverviewApplication Description Kroo Bank is charting the future of banking through technology, data, and innovation. As a digital first bank, we use data science to help us make smarter decisions, improve customer outcomes, and build products that customers trust and love. The rapid pace of change within fintech creates exciting opportunities to apply advanced analytics, machine learning, and experimentation to real business challenges. As a Data Scientist, you will play a key role in helping Kroo use data more effectively across a wide range of business areas, partnering with teams across Product, Risk, Operations, Compliance, and Engineering. This role is responsible for building, evaluating, and deploying data science solutions that support strategic decision making and improve customer experiences. You will work on high impact initiatives across areas such as credit risk, fraud prevention, customer engagement, and operational efficiency, helping the business make informed decisions through robust analysis, experimentation, and modelling. How you'll contribute: - 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. Requirements Required skills and behaviours: - 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 basic 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. Benefits Hybrid Working At Kroo Bank, we have a hybrid/ flexible policy that gives both individuals and teams a lot of freedom when it comes to using the office space to boost productivity. Our London office is a great resource to collaborate and candidates should be able to attend 1-2 days per week regularly to align with how we work at the moment. Diversity and Inclusion We wholeheartedly uphold our commitment to fostering a diverse and inclusive workplace. Every employee is highly regarded, respected, and supported without any form of judgement or prejudice. We consider Diversity, Equality, and Inclusion as fundamental pillars guiding our path in all aspects of our bank. We also ensure that reasonable adjustments are made available to all candidates throughout the recruitment process. To all Recruitment Agencies At Kroo Bank, agency resumes are strictly prohibited. Do not submit agency resumes or forward them to our job advertisements or Kroo Bank employees. Be aware that Kroo Bank will not assume any responsibility for fees incurred due to unsolicited resumes. To ensure a fair and efficient application process, all candidates are kindly requested to submit their applications directly through the advertised platform. We kindly ask that you refrain from reaching out to the company or its employees via email, LinkedIn, or any other communication channels for inquiries or updates. Please note that any attempts to contact us through these channels will not receive a response. Thank you for your understanding and cooperation.

Related Categories

Related Job Pages

More Data Scientist Jobs

Flinks logo

Senior Data Scientist

Flinks

We deliver tools for financial innovation to businesses—big and small

Data Scientist2 days ago
Full TimeRemoteTeam 51-200Since 2016H1B No Sponsor

Own and deploy machine-learning models from inception to monitoring, ensuring model quality and performance. Collaborate across teams to integrate model outputs into various financial systems and drive impactful business outcomes.

Canada
GXO Logistics, Inc. logo

Data Science Apprentice

GXO Logistics, Inc.

Logistics at full potential.

Data Scientist2 days ago
Full TimeRemoteTeam 10,001+H1B No Sponsor

• Support the collection, analysis and interpretation of operational data across multiple site operations • Build dashboards and visualisations (Power BI) to track performance and trends • Assist with root cause analysis and data-driven problem solving • Identify opportunities to increase productivity, efficiency and performance • Contribute to digital and system projects and the adoption of key tools • Work with multiple stakeholders across finance, operations and continuous improvement to turn data into actionable insights • Maintain and update SharePoint sites and content libraries for accurate information sharing

United Kingdom
£28K / year
Full TimeRemoteTeam 11-50H1B No Sponsor

• Act as the Subject Matter Expert (SME), drive the end-to-end building and execution of our Risk & Underwriting AI models, directly translating actuarial and healthcare financial risk expertise into high-performance AI models and rigorous evaluation frameworks. • Set the technical roadmap and lead the development of ML models focused on healthcare financial risk stratification and financial underwriting. • Establish best practices for model building, model validation, and rigorous back testing/benchmarking across the data science organization to drive high performance models, while maintaining stability and alignment of models. • Mentor junior data scientists, fostering a culture of rigorous research, high-quality engineering, and innovation. • Partner with clinicians to translate medical knowledge into data-driven hypotheses and with Product/Executive teams to align technical capabilities with market opportunities. • Work with Engineering to design the next generation of our platform’s quality and extensibility, ensuring it remains performant for millions of patients. • Represent Prealize Health’s technical expertise to external strategic partners and stay at the forefront of literature in ML, Actuarial Science, and Biostatistics.

United States
$160K - $190K / year
Analytica logo

Data Scientist – NLP

Analytica

Data-driven consulting and technology services

Data Scientist2 days ago
Full TimeRemoteTeam 51-200H1B No Sponsor

• Pre-processing - Demonstrate the skills and experience to collect, clean, and prepare data sets for input into a computational model using Python • Strong candidates will explain various methods you have applied using common pre-processing functions such as stop word removal, stemming, lemmatization, and tokenization • Feature Engineering and Attribute Evaluation - Candidate must demonstrate experience with NLP feature engineering methods such as TF-IDF, word2vec, GloVe, and FastText identifying the key determinants for modeling that exist in the business process and within existing data sets as well as selecting evaluation protocols (model techniques) • Modeling - Candidates will have practiced skills and experience selecting classification modeling techniques to fit the business problem. Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc. • Validation - Strong candidates will describe their experience with investigating, reporting, and justifying model results • Visualization- Experience in presenting the results of their modeling activities, depicting the insights realized, and explaining the relevance of their results to the organization’s business challenges

United States