Keyrus

Data Engineer

• Design, develop, and maintain robust, scalable, and efficient data pipelines in a GCP environment, with a focus on BigQuery
• Implement and manage data ingestion processes from ERP systems, files, and APIs
• Create, optimize, and document dimensional data models and analytical solutions within a Lakehouse architecture
• Orchestrate and monitor ETL/ELT processes using Informatica Cloud
• Partner with Analytics, Data Science, and Product teams to enable data-driven analyses and solutions
• Ensure data quality, governance, and security throughout the data lifecycle
• Apply data engineering best practices, including version control, automation, and testing
• Optimize queries and the performance of analytical environments
• Manage requests and align expectations with various stakeholders, including leadership and business teams
• Provide technical contributions to the evolution of data practices, processes, and architecture

Senior Data Engineer, GCP

Data Scientist

• Transform complex business challenges into scalable, modern, and results-driven data solutions
• Develop and evaluate statistical and Machine Learning models
• Build Generative AI solutions using RAG, embeddings, vector search, and prompt engineering
• Prepare data, perform feature engineering, and train and validate models
• Take analytical or AI solutions from prototype to production
• Ensure quality, monitoring, security, performance, cost efficiency, and governance throughout the model lifecycle
• Work with structured and unstructured data
• Collaborate with Product Managers, Architects, Engineers, Data Governance teams, and business subject-matter experts
• Translate real-world needs into scalable and reliable solutions
• Contribute to Keyrus Data Science, Machine Learning, and Artificial Intelligence projects

Senior Data Scientist – Artificial Intelligence

• Collect, process, and analyse structured and unstructured datasets using Python, SQL, and modern data science techniques
• Develop, validate, and deploy machine learning and statistical models for forecasting, customer analytics, and predictive business use cases
• Perform feature engineering, data preparation, and model optimisation
• Design and maintain analytical workflows and data pipelines, collaborating with Data Engineering teams when required
• Identify trends, patterns, risks, and opportunities in complex datasets
• Translate analytical findings into actionable recommendations and present results to technical and non-technical stakeholders
• Collaborate with clients, business stakeholders, and cross-functional teams to deliver data-driven solutions
• Support data science best practices, modelling methodologies, and reusable analytical frameworks
• Apply predictive analytics, customer analytics, and advanced statistical techniques to business challenges
• Contribute to client-facing analytics projects from discovery through implementation

• Work as a Junior Data Analyst on projects that connect technology, data, and business
• Work with Snowflake and data technologies
• Participate in the development, enhancement, and support of data solutions
• Support Cloud Data Platform projects
• Develop and support data solutions used across different business contexts
• Perform activities related to processes, documentation, testing, and data quality validation
• Investigate issues and seek solutions
• Share knowledge and collaborate with different specialties, functions, and geographies

Junior Data Engineer – Snowflake

• Develop automations and data pipelines using Python, PySpark, and SQL to modernize processes and reduce manual work
• Architect and develop end-to-end Machine Learning models, from data exploration and feature engineering through deployment, production monitoring, and retraining
• Work with large volumes of data in distributed environments, ensuring performance, quality, and traceability
• Work on Fraud, AML, Lead Scoring, and Churn projects, creating business-focused data and ML solutions
• Serve as a technical reference, supporting junior professionals through code reviews, best practices, and guidance in Data Science and ML
• Lead meetings and technical interactions in English
• Transform legacy processes into automated, robust, and scalable solutions

Senior Data Scientist – Fluent English

Strategy

• Lead strategic analysis and portfolio management
• Support planning, business intelligence, and product initiatives
• Analyze performance, results, and opportunities across the financial products portfolio
• Support decisions related to product growth, profitability, and evolution
• Work with financial products, particularly consumer credit cards, payment solutions, lending, or retail banking
• Transform analyses and data into strategic insights and business direction
• Identify results, growth levers, gaps, and opportunities when monitoring portfolio performance
• Develop diagnostics, hypotheses, analyses, and executive recommendations
• Influence decision-making and build trusted relationships with stakeholders

Senior Strategy Analyst

Business Analyst

• Understand and translate business questions into structured analytical approaches
• Conduct end-to-end analysis to support commercial and D2C initiatives
• Write, optimise and use SQL queries to investigate business questions and work with relevant datasets
• Provide analytical support across pricing, promotions and experimentation
• Support analysis and interpretation of experiments and A/B tests where relevant
• Translate analytical findings into clear, actionable business insights
• Independently structure analytical problems, determine appropriate approaches and deliver high-quality outputs
• Communicate progress, findings and next steps with the wider team
• Collaborate with the Analytics team to increase analytical capacity and accelerate insight delivery

Senior Business Analyst

• Understand and translate business questions into structured analytical approaches
• Conduct end-to-end analysis to support commercial and D2C initiatives
• Write, optimise and use SQL queries to investigate business questions and work with relevant datasets
• Provide analytical support across pricing, promotions and experimentation
• Support the analysis and interpretation of experiments and A/B tests
• Translate analytical findings into clear, actionable business insights
• Work independently to structure analytical problems, determine appropriate approaches and deliver high-quality outputs
• Communicate progress, findings and next steps clearly with the wider team
• Collaborate with the Analytics team to increase analytical capacity and accelerate insight delivery

Consultant

• Develop and maintain Tableau dashboards, workbooks, and data extracts
• Translate business requirements into effective BI and reporting solutions
• Design intuitive data visualisations that drive adoption and business value
• Develop and optimise SQL queries, data sources, and dashboard performance
• Apply data modelling and ETL concepts to support reporting requirements
• Support Tableau migration and analytics modernisation initiatives
• Collaborate with stakeholders to deliver high-quality analytics solutions
• Advise clients on data visualisation, BI best practices, and analytics adoption
• Contribute to delivery within Agile/Scrum environments

Tableau Consultant

AI Engineer

• Design and implement serverless and cloud-native architectures on AWS
• Build and deploy Generative AI applications using Amazon Bedrock, foundation models, Knowledge Bases, Agent capabilities, guardrails, and related AWS services
• Develop AI applications and services using Python and Boto3
• Design and implement production-grade Retrieval-Augmented Generation solutions using Amazon OpenSearch, Bedrock Knowledge Bases, vector search technologies, and LLMs
• Design and optimise RAG pipelines, including chunking strategies, retrieval optimisation, metadata filtering, and context management
• Implement semantic search solutions using Amazon OpenSearch
• Design and build agent-based architectures using Bedrock Agents and AgentCore capabilities
• Develop prompt engineering frameworks and reusable prompting strategies
• Implement LLM evaluation methodologies, including LLM-as-a-Judge and automated evaluation frameworks
• Design model routing and inference optimisation strategies
• Apply GenAI observability, monitoring, and operational best practices
• Contribute to AI governance, evaluation, and responsible AI initiatives
• Support the industrialisation of AI solutions into scalable production environments
• Collaborate with Cloud Engineers, Data Engineers, Architects, and client stakeholders
• Contribute to AI engineering best practices, standards, and reusable frameworks

Senior Data Engineer, GCP

Senior Data Scientist – Artificial Intelligence

Data Scientist

Junior Data Engineer – Snowflake

Senior Data Scientist – Fluent English

Senior Strategy Analyst

Senior Business Analyst

Senior Business Analyst

Tableau Consultant

Senior AWS AI Engineer