Data Scientist

Albany Beck; Dublin; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Albany Beck, a specialist Financial Services consultancy, is seeking an experienced Data Scientist to design and deliver AI-driven solutions across the organisation. You will translate business challenges into practical AI models, support LLM-based applications and intelligent digital coworkers, and help scale AI initiatives within enterprise governance frameworks.

You will contribute to the design, development and deployment of AI capabilities, working on governance, data models and reusable

Qualifications

• Proven experience in Data Science, Machine Learning or AI roles.
• Experience with LLMs, generative AI, prompt engineering.
• Experience with Microsoft Copilot Studio and Power Platform.
• Experience with Azure AI services and enterprise AI platforms.
• Strong stakeholder management and communication skills.
• Ability to operate independently in a developing AI environment.

Responsabilités

• Design, develop and implement AI and ML solutions to address business challenges and improve operational efficiency.
• Develop LLM-based applications and intelligent workflows using LangGraph and related frameworks.
• Support digital coworkers and AI-powered assistants as part of enterprise AI programmes.
• Build AI solutions using Microsoft Copilot Studio and related Microsoft technologies.
• Develop prototypes and proof-of-concept solutions and transition them to production.

Connaissances

Python programming

LLMs

AI governance

Data analysis

Stakeholder management

Problem solving

Cloud computing

Communication skills

Outils

LangGraph

Copilot Studio

Power Platform

Azure AI

Description du poste

Albany Beck is a specialist Financial Services Consultancy helping institutions deliver complex change and transformation while building the internal capability to sustain it. We combine subject matter expertise with innovative delivery models that help clients scale efficiently, while offering meaningful, long-term career opportunities to our people. At Albany Beck, you’ll be choosing to work with an organisation that’s passionate about your learning journey and committed to your professional and personal development.

Role Overview

We are seeking an experienced Data Scientist to support the development and implementation of AI-driven solutions, intelligent automation and digital workforce initiatives across the organisation.

The successful candidate will play a key role in translating business challenges into practical AI solutions, supporting the development of LLM-based applications and intelligent digital coworkers, and identifying opportunities to improve business processes through data science, advanced analytics and AI technologies.

Working across enterprise-level AI programmes and business-led initiatives, the Data Scientist will contribute to the design, development, testing and deployment of AI capabilities, helping move solutions from proof of concept into production. The role will also support the development of robust AI governance frameworks, data models and reusable technical capabilities to enable the responsible and scalable adoption of AI.

This is an opportunity to join a growing AI function at an early stage of its maturity, with significant scope to influence the organisation’s AI strategy, technical capabilities and approach to intelligent automation.

Key Responsibilities

• Design, develop and implement AI and machine learning solutions to address business challenges and improve operational efficiency.
• Develop LLM-based applications, AI agents and intelligent workflows using technologies such as LangGraph and other relevant large language model frameworks.
• Support the development of digital coworkers and AI-powered assistants as part of enterprise-wide AI programmes.
• Build and enhance business-led AI solutions using Microsoft Copilot Studio and associated Microsoft technologies.
• Develop prototypes and proof-of-concept solutions, evaluating their feasibility, performance and potential business value before production deployment.
• Support the transition of successful AI use cases into production, including testing, performance monitoring and continuous improvement.

AI Use Case Identification & Delivery

• Work with business stakeholders to identify, assess and prioritise AI opportunities across functions and processes.
• Translate business requirements into technical designs, AI models and practical solutions.
• Evaluate potential use cases based on business value, technical feasibility, implementation complexity, risk and scalability.
• Support the development of an AI use case pipeline, helping establish a sustainable approach to AI innovation and delivery.
• Collaborate with process engineering and transformation teams to identify opportunities for intelligent automation and process optimisation.
• Develop data models, statistical models and predictive analytics solutions to support decision-making and business performance.
• Explore, prepare and analyse structured and unstructured data to identify patterns, trends and opportunities.
• Apply appropriate analytical and machine learning techniques to generate actionable insights.
• Work with data engineering and analytics colleagues to improve data quality, accessibility and suitability for AI applications.
• Support the integration of data science outputs into reporting, business processes and AI-enabled solutions.
• Contribute to the development and implementation of AI governance frameworks, standards and controls.
• Support responsible AI practices covering data privacy, security, transparency, explainability and human oversight.
• Help assess model performance, reliability, bias and operational risks.
• Establish appropriate testing, validation, monitoring and documentation practices for AI solutions.
• Work with risk, compliance, technology and business stakeholders to ensure solutions align with relevant organisational policies and regulatory expectations.

Process Transformation & Digital Workforce

• Identify opportunities to redesign and optimise business processes through AI, automation and advanced analytics.
• Support the development of digital workforce capabilities that augment employee productivity and improve service delivery.
• Collaborate with business and technology teams to embed AI solutions into existing workflows and operating models.
• Measure the effectiveness of AI initiatives against agreed business outcomes, including productivity, quality, efficiency and user adoption.
• Proven experience in a Data Science, Machine Learning, Applied AI or equivalent technical role.
• Practical experience developing and deploying data science, machine learning or AI solutions.
• Strong Python programming skills and experience with relevant data science libraries and frameworks.
• Experience working with LLMs, generative AI, prompt engineering, retrieval-augmented generation (RAG), AI agents or comparable technologies.
• Understanding of agent orchestration frameworks, ideally LangGraph or similar technologies.
• Experience developing AI prototypes and translating them into reliable, production-ready solutions.
• Strong analytical, statistical and problem-solving skills.
• Experience in data preparation, feature engineering, model development and evaluation.
• Understanding of data modelling, data pipelines and the data foundations required to support AI solutions.
• Awareness of AI governance, responsible AI, model risk and data privacy considerations.
• Strong stakeholder management and communication skills, with the ability to explain technical concepts to non-technical audiences.
• A pragmatic, delivery-focused mindset, with the ability to operate independently in a developing AI environment.
• Experience with Microsoft Copilot Studio and the Microsoft Power Platform.
• Experience with Azure AI services, Microsoft Foundry or equivalent enterprise AI platforms.
• Experience with cloud-based data and AI environments.
• Knowledge of API integration, software engineering best practices, version control, automated testing and deployment processes.
• Experience with process mining, intelligent automation or business process re-engineering.
• Experience in financial services or another regulated industry.
• Experience implementing AI solutions within enterprise governance and security frameworks.