AI Solutions Lead

Position: AI Solutions Lead – Business Development (Bleckmann)

• Lead and maintain the delivery of an AI‑based lead classification and scoring model that is co‑created with an external party.
• Ensure model performance through validation, retraining, and deployment best practices.
• Translate business goals into machine‑learning use cases and AI‑powered solutions.
• Coordinate with internal teams to integrate and expand the model into business processes and data pipelines.
• Act as a key driver for scaling AI adoption in other parts of the business.
• Identify, prioritise, and lead additional AI and ML initiatives across the organization.
• Ensure ethical and compliant AI usage aligned with data governance and quality standards.
• Present insights and progress to technical and non‑technical stakeholders.
• Take ownership of an existing AI lead scoring/classification model delivered by consultants; monitor, validate, and enhance model performance through regular retraining and optimisation.
• Expand the model with new features by managing and coordinating data and engineering experts.
• Ensure integration of the model into data pipelines and business processes.
• Collaborate with Data Engineers, Analysts, and Business Stakeholders to deliver and align model outcomes with business goals.
• Translate business requirements into AI/ML problems and vice versa.
• Represent AI capabilities in cross‑functional meetings; lead conversations around feasibility, business value and prioritisation of AI solutions.
• Identify and lead new AI/ML initiatives within the organization, focusing on new business and client retention.
• Promote best practices in AI development, governance and ethical considerations.
• Evaluate and experiment with new tools (AutoML, MLOps platforms).
• Propose and prototype AI solutions aligned with strategic goals.
• Lead discussions on model governance, scalability and long‑term roadmap.
• Develop centre of expertise on AI & governance within the organisation.
• Maintain adherence to AI governance and quality standards.

• Technical
  
  Competencies:
  
  
  • Strong proficiency in Python and SQL for data manipulation, modelling and scripting.
  • Hands‑on experience with machine‑learning libraries and frameworks (Scikit‑learn, Tensor Flow, PyTorch).
  • Experience with cloud platforms (AWS, Azure, GCP) and containerisation tools (Docker, Kubernetes).
  • Familiarity with data‑pipeline orchestration tools such as Airflow or dbt.
  • Good understanding of data modelling, data warehouses (Snowflake, Redshift) and API integrations.
  • Fluency in English;
    Dutch is a plus.
• Personal Qualities &
  
  Skills:
  
  
  • Proactive, analytical, problem‑solving mindset.
  • Hands‑on, independent, comfortable taking ownership of projects.
  • Capable of translating business problems into data‑driven solutions.
  • Strong communicator bridging technical teams and business stakeholders.
  • Adaptable, collaborative, thrives in fast‑paced, agile environment.
  • Able to coach junior data scientists or engineers.
  • Passionate about AI, continuously seeks to stay up‑to‑date with new tools and techniques.
• Experience &
  
  Education:
  
  
  • Master’s degree in AI, Data Science, Computer Science, Engineering, Business Information Management or related field.
  • 3–5 years of experience in developing, deploying and managing AI/ML models in production.
  • Proven experience in leading and implementing AI projects and working cross‑functionally with both business and technical teams.
  • Proven ability to drive change in the organisation and scale adoption of AI solutions.
• Nice to Have:
  • Experience delivering AI/ML models into production, classification or scoring domains.
  • Involvement in setting up internal AI capabilities or Center of Excellence.
  • Experience with visualization tools such as Tableau or Power BI.
  • Familiarity with data governance, security, and version control best practices.