Lead Data Scientist – ML & AI-Powered Risk Intelligence

Archer · Recruitment agency
Full-time•Data engineering•Dublin, Ireland · Remote within Ireland
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At a glance

Employment type
Full-time
Workplace
Remote

Technologies & skills

Primary technologies

PythonPHP

Other technical skills

SQL

What you'll be doing

Lead Data Scientist role at a global AI-powered SaaS company, building ML models and data pipelines for risk intelligence. First Data Scientist in Ireland with rapid progression into leadership. Fully remote, collaborating with international teams, and significant ownership of projects from data prep to production deployment.

  • Build and maintain machine learning models and data pipelines
  • Analyse complex datasets to develop predictive and classification models
  • Improve data quality, automation and modelling processes
  • Translate business challenges into scalable AI and ML solutions
  • Deploy, monitor and optimise machine learning models in production
  • Research and apply new AI tools and techniques

Key requirements

Must-have

  • Strong experience in Data Science or Machine Learning
  • Strong Python skills
  • Strong SQL, database and data engineering fundamentals
  • Experience deploying machine learning models into production
  • Strong commercial and problem-solving mindset

Nice-to-have

  • Leadership, mentoring or technical leadership experience

Role signals

Technical focus
Data Science, Machine Learning, AI, Data Engineering
Leadership
Mentoring
Hands-on vs management
Hands-on

Full job description

Lead Data Scientist – ML & AI-Powered Risk Intelligence

- Join a global AI-powered SaaS leader transforming risk intelligence

- Be the first Data Scientist in Ireland, with rapid progression into leadership

- Build machine learning models with real business impact

- Work fully remotely with international teams across the globe

An exciting opportunity has opened for a Lead Data Scientist to join a global technology organisation developing an AI-powered SaaS platform for risk intelligence.

This hands-on role focuses on building machine learning models, data pipelines and scalable analytics solutions that deliver predictive insights across financial, cyber, operational, ESG and compliance risk.

As the first Lead Data Scientist based in Ireland, you will work closely with Product, Engineering and Data teams internationally, while having the opportunity to quickly grow into leading the Data Science capability in Ireland. Previous leadership, technical leadership, or mentoring experience would be a big advantage.

This is an excellent opportunity for an ambitious Data Scientist looking to combine hands-on technical work with significant ownership, visibility and a clear path into leadership within a growing international AI business.

Why This Role Stands Out

  • Be the first Data Scientist in Ireland and help establish the local Data Science capability

  • Clear and rapid progression into leading the Data Science function in Ireland

  • Work on an AI-powered SaaS platform used by global organisations

  • Own projects from data preparation and modelling through to production deployment

  • Collaborate with international Product, Engineering and Data teams

What You’ll Be Doing

  • Build and maintain machine learning models and data pipelines

  • Analyse complex datasets to develop predictive and classification models

  • Improve data quality, automation and modelling processes

  • Translate business challenges into scalable AI and ML solutions

  • Deploy, monitor and optimise machine learning models in production

  • Research and apply new AI tools and techniques

What You Bring

  • Strong experience in Data Science or Machine Learning with strong Python skills

  • Strong SQL, database and data engineering fundamentals

  • Experience deploying machine learning models into production

  • Strong commercial and problem-solving mindset

  • Leadership, mentoring or technical leadership experience is highly desirable

Package & Benefits

  • Up to €100,000 base salary

  • Up to 15% annual bonus

  • Equity package!

  • Fully remote anywhere in Ireland

  • International working environment with teams across the globe

  • Clear opportunity to progress into leading the Data Science function in Ireland

Interested in joining a global AI-powered SaaS platform, building solutions that solve complex business problems, and having the opportunity to lead the Data Science capability in Ireland?

Contact Serena Akbib on +353 1 960 9972 or send your CV to .

Interview prep pack

Grounded in this listing. Use it to prepare examples before you apply.

Your interview focus

Based on this listing, the Lead Data Scientist role focuses on building and deploying machine learning models for an AI-powered SaaS risk intelligence platform, with a strong emphasis on hands-on technical work, collaboration with international teams, and rapid progression into leadership within Ireland.

  • Hands-on ML Model Deployment·High
  • Data Engineering and Automation·High
  • Leadership Potential·Medium
  • Cross-functional Collaboration·Medium

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

  1. Review and Summarize Key ML Projects

    0–8 min

    Select 2-3 relevant projects that showcase your experience with model development, deployment, and business impact; prepare concise summaries.

  2. Refresh Data Engineering and Automation Skills

    8–14 min

    Revisit your experience with Python, SQL, and data pipeline tools; be ready to discuss technical details and improvements made.

  3. Prepare Leadership and Mentoring Examples

    14–20 min

    Identify situations where you led or mentored others, focusing on your approach and outcomes.

  4. Research AI/ML Trends in Risk Intelligence

    20–25 min

    Read recent articles or case studies on AI applications in risk intelligence to discuss industry relevance.

  5. Draft Role-Specific Questions

    25–30 min

    Prepare thoughtful questions about the team, challenges, and growth opportunities to ask during the interview.

Likely questions

, 6 items

Priority reflects how strongly this topic is emphasised in the job listing, not whether it will be asked.

Talking points

, 5 items

  • End-to-End Machine Learning Model Lifecycle

    You will need to demonstrate experience in building, deploying, monitoring, and optimizing ML models in production environments; prepare examples that show your technical depth and impact.

  • Data Engineering and Pipeline Automation

    The role requires building and maintaining data pipelines and improving automation; be ready to discuss your approach to scalable data workflows and data quality improvements.

  • Translating Business Problems into ML Solutions

    You will be expected to convert complex business challenges into actionable AI/ML projects; prepare stories where you identified business needs and delivered measurable results.

  • Collaboration with International and Cross-functional Teams

    Success in this role depends on working closely with Product, Engineering, and Data teams globally; have examples of effective communication and teamwork in diverse, remote settings.

  • Technical Leadership and Mentoring

    The listing highlights rapid progression into leadership and values mentoring experience; be ready to discuss how you have led, coached, or influenced others technically.

What to research

, 4 items

  • Recent Machine Learning Projects

    Review your most impactful ML projects, focusing on end-to-end delivery, deployment, and business outcomes.

  • Data Engineering Tools and Best Practices

    Refresh your knowledge of data pipeline automation, data quality frameworks, and relevant tools (e.g., Python, SQL).

  • Leadership and Mentoring Experience

    Prepare examples of how you have led, mentored, or influenced others in technical settings.

  • AI and ML Trends in Risk Intelligence

    Research current AI/ML applications in financial, cyber, operational, ESG, and compliance risk domains.

Questions to ask

, 6 items
  1. What are the immediate priorities for the Data Science function in Ireland over the next 6-12 months?

    Why ask this? To understand expectations and how you can make an early impact.

  2. How does the Data Science team collaborate with Product, Engineering, and Data teams internationally?

    Why ask this? To clarify cross-functional workflows and communication practices.

  3. What are the main challenges the company faces in deploying and scaling ML models for risk intelligence?

    Why ask this? To identify technical and business obstacles you may encounter.

  4. What opportunities exist for professional growth and leadership development within the Data Science function?

    Why ask this? To assess the path for progression and leadership responsibilities.

  5. How is success measured for Data Science projects in this organization?

    Why ask this? To align your work with the company’s definition of impact and value.

  6. What tools and technologies are currently used for data pipelines and model deployment?

    Why ask this? To understand the technical environment and where your skills fit.

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Apply NowApply before: 4 Nov 2026