Data Scientist

About Albany Beck

Albany Beck is a specialised consultancy in Financial Services, dedicated to assisting institutions in executing complex change and transformation initiatives. They focus not only on delivery but also on building clients' internal capabilities for sustainable growth. The company champions continuous learning and is committed to the professional and personal advancement of its employees.

Role Overview

We are looking for a seasoned Data Scientist to spearhead the creation and rollout of AI-driven applications, intelligent automation, and digital workforce solutions throughout the organization. The successful candidate will convert business challenges into actionable AI-based strategies, focus on developing large language model (LLM) applications, digital coworkers, and identify areas for enhancing business processes through advanced analytics and AI technology.

Collaborating on enterprise-wide AI initiatives and business-directed projects, the Data Scientist will be instrumental in designing, developing, validating, and deploying AI capabilities, progressing them from prototype stages to production. The role also entails contributing to robust AI governance, crafting data models, and developing reusable technical assets to promote responsible and scalable AI integration.

This position offers an exciting opportunity to join a nascent AI division with ample potential to shape AI tactics, build technical expertise, and drive intelligent automation within the company.

Key Responsibilities

• Create and implement AI and machine learning systems that address business needs and increase operational efficiency.
• Develop LLM-based tools, AI agents, and intelligent workflows using frameworks such as LangGraph and other relevant large language model platforms.
• Assist in building digital coworkers and AI-powered assistants as part of broad AI initiatives across the enterprise.
• Enhance AI solutions using Microsoft Copilot Studio and associated Microsoft technologies tailored to business requirements.
• Construct prototypes and proof-of-concept models, assess their viability and potential impact before full deployment.
• Facilitate the shift of successful AI initiatives into live environments including rigorous testing and continuous optimization.
• Collaborate with stakeholders to identify, evaluate, and prioritize AI opportunities and use cases across various functions.
• Convert business needs into technical AI solutions, models, and actionable designs.
• Assess the feasibility, risk, complexity, and scalability of AI applications to prioritize their delivery.
• Develop and manage an AI use case pipeline to support sustained innovation and deployment.
• Work closely with process engineering and business transformation teams to find opportunities for intelligent automation and process enhancements.
• Design data, statistical, and predictive models to inform decision-making and improve performance.
• Analyze structured and unstructured data to detect patterns, trends, and business opportunities.
• Apply suitable analytical methods and machine learning techniques to generate insights for actionable outcomes.
• Partner with data engineering and analytics units to enhance data quality, accessibility, and AI readiness.
• Integrate data science findings into reporting, workflows, and AI-driven processes.
• Participate in the creation and enforcement of AI governance frameworks, ensuring compliance with standards and controls.
• Advocate responsible AI practices focusing on data privacy, security, transparency, and human oversight.
• Evaluate the performance, bias, and risks associated with AI models and solutions.
• Implement thorough testing, validation, and documentation protocols for AI products.
• Engage with risk, compliance, IT, and business departments to align AI implementations with organizational policies and regulatory requirements.
• Identify and support opportunities to re-engineer business processes through AI, automation, and advanced analytics.
• Help build digital workforce capabilities to boost employee efficiency and service quality.
• Coordinate with technology and business units to embed AI innovations into existing operational models.
• Measure success against business metrics such as productivity, quality, efficiency, and adoption rates.

Essential Skills & Experience

• Established background in Data Science, Machine Learning, Applied AI or a closely related technical discipline.
• Hands-on experience in developing and deploying AI, machine learning, and data science solutions.
• Proficiency in Python programming and familiarity with its data science libraries and frameworks.
• Experience with large language models, generative AI, prompt engineering, retrieval-augmented generation (RAG), AI agents, or similar cutting-edge AI technologies.
• Knowledge of agent orchestration platforms, particularly LangGraph or related systems.
• Capability in creating AI prototypes and converting them into dependable production-ready solutions.
• Strong analytical acumen paired with statistical and problem-solving skills.
• Expertise in data preparation, feature engineering, modeling, and performance evaluation.
• Understanding of data modeling concepts, pipeline architectures, and foundational data requirements to support AI applications.
• Awareness of AI governance, ethical AI principles, model risk management, and data privacy concerns.
• Excellent stakeholder engagement and communication skills, effectively translating technical details for non-technical audiences.
• A solution-oriented mindset with the ability to work autonomously within an evolving AI setting.

Desirable Skills & Experience

• Experience with Microsoft Copilot Studio and Microsoft Power Platform.
• Familiarity with Azure AI offerings, Microsoft Foundry, or equivalent enterprise AI environments.
• Knowledge of cloud-based data and AI ecosystems.
• Understanding of API integrations, software engineering best practices, version control systems, automated testing, and deployment methodologies.
• Background in process mining, intelligent automation, or business process re-engineering.
• Experience within financial services or regulated sectors.
• Proven track record implementing AI solutions in governance and security-compliant frameworks.