Lead Data Scientist – ML & AI-Powered Risk Intelligence!
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At a glance
- Employment type
- Full-time
- Workplace
- Remote
- Category
- Data engineering
What you'll be doing
Lead Data Scientist role at a global AI company focused on ML-powered risk intelligence. Hands-on position with opportunities to build models, develop data pipelines, and deploy solutions. Fast-track to leadership, with potential to build and lead the Data Science function in Ireland. Fully remote within Ireland.
Key requirements
Must-have
- Experience in Data Science or Machine Learning
- Strong Python skills
- Strong SQL, database and data engineering fundamentals
- Experience deploying machine learning models into production
Role signals
- Technical focus
- Data Science, Machine Learning, Model Deployment, Data Engineering
- Leadership
- Mentoring
- Hands-on vs management
- Hands-on
Similar jobs
Full job description
Lead Data Scientist – ML & AI-Powered Risk Intelligence!
- Join a global AI business with the mindset and ambition of a startup
- Build cutting-edge machine learning solutions with real commercial impact
- Fast-track your career towards leading Data Science in Ireland and building your own team
An exciting opportunity has opened for a Data Scientist to join a global technology organisation developing next-generation AI-powered risk intelligence solutions. This is a hands-on, high-impact role for someone who wants to build, innovate and take ownership in a fast-moving technology environment.
The business is investing in AI and machine learning to transform how organisations understand and manage financial, cyber, operational, ESG and compliance risk. You’ll have the opportunity to build models, develop data pipelines and turn complex datasets into intelligent products used by global enterprise clients.
Working closely with Product, Engineering and Data teams, you’ll have the freedom to challenge existing approaches, experiment with new technologies and take ideas from concept through to production. This is an opportunity to make a tangible impact on the product, influence technical direction and help shape how AI is developed and deployed across the business.
What makes this opportunity particularly exciting is the potential for rapid progression into a leadership role. Rather than joining a large, established Data Science department with a fixed career path, you’ll have the opportunity to help build the function in Ireland as the business grows. For an ambitious Data Scientist with a startup mindset, this could be the opportunity to progress towards leading Data Science, shaping the technical roadmap, hiring your own team and taking ownership of the function.
Why This Role Stands Out
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Fast-track to leadership: A genuine opportunity to progress towards leading the Data Science function in Ireland as the business scales
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Build your own team: Help shape the future team, establish best practices and develop a high-performing Data Science capability
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Startup mentality, global reach: Enjoy the ownership, autonomy and pace of a growing technology business with global enterprise customers
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End-to-end ownership: Take projects from initial experimentation and data preparation through to production deployment
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Influence product strategy: Work directly with Product and Engineering to turn innovative AI concepts into commercially valuable solutions
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Accelerate your career: Develop your technical expertise while gaining exposure to strategic decision-making and future people leadership
What You Bring
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Experience in Data Science or Machine Learning, with strong Python skills
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Strong SQL, database and data engineering fundamentals
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Experience deploying machine learning models into production
Package & Benefits
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Up to €100,000 base salary
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Up to 15% annual bonus
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Equity package
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Fully remote role based in Dublin, Ireland
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Opportunity for accelerated career progression towards leading the Data Science function in Ireland and building your own team
Interested in building next-generation AI solutions, taking ownership and accelerating your journey towards Data Science leadership? 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 ML/AI-powered risk intelligence solutions, with a strong emphasis on hands-on technical work, end-to-end project ownership, and the opportunity to progress into a leadership position as the function grows in Ireland.
- Hands-on technical expertise·High
- Leadership and team-building potential·High
- End-to-end project ownership·High
- Collaboration with cross-functional teams·Medium
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review and Summarize Key ML Projects
0–8 minSelect 1-2 relevant projects where you led end-to-end ML development and deployment, and prepare concise summaries.
Refresh Python and SQL Skills
8–15 minPractice advanced Python for data science and SQL queries, focusing on areas relevant to data engineering and model deployment.
Reflect on Leadership and Team Building Experience
15–20 minPrepare examples of mentoring, establishing best practices, or contributing to team growth.
Research the Company’s AI and Risk Intelligence Focus
20–25 minFamiliarize yourself with the company’s products, target industries, and recent developments in AI-powered risk intelligence.
Prepare Role-Specific Questions
25–30 minDraft thoughtful questions about team structure, technical challenges, and leadership opportunities to ask during the interview.
Talking points
, 5 itemsEnd-to-End Machine Learning Project Delivery
You should be able to discuss how you have taken ML projects from data preparation through to production deployment, as this role emphasizes full project ownership.
Building and Scaling Data Pipelines
Demonstrating experience with robust data engineering and pipeline construction will show your ability to handle complex datasets and support intelligent product development.
Deploying Models in Production Environments
The listing highlights deploying ML models into production, so be ready to share examples of your deployment strategies, challenges faced, and how you ensured reliability and scalability.
Technical Collaboration and Influence
You will work closely with Product and Engineering teams; prepare examples of how you have influenced product strategy or collaborated cross-functionally to deliver impactful solutions.
Leadership Potential and Team Building
Since the role offers a path to leadership, be prepared to discuss your vision for building a high-performing data science team and establishing best practices.
What to research
, 4 itemsPython and SQL Technical Review
Brush up on advanced Python for data science and SQL/database fundamentals, as these are explicitly required.
Machine Learning Model Deployment
Prepare to discuss your experience deploying ML models into production, including tools, processes, and challenges.
Data Pipeline Design
Review your experience building and maintaining data pipelines, focusing on scalability and reliability.
Leadership and Team Building
Reflect on your approach to building teams, establishing best practices, and mentoring others, as the role offers rapid progression to leadership.
Questions to ask
, 6 itemsWhat are the immediate priorities for the Data Science function in Ireland over the next 6-12 months?
Why ask this? Clarifies expectations and helps you understand the short-term impact you can make.
How does the team currently collaborate with Product and Engineering to deliver AI-powered solutions?
Why ask this? Gives insight into cross-functional workflows and your potential influence on product strategy.
What are the biggest technical challenges the team is facing with model deployment or data pipelines?
Why ask this? Helps you assess where your skills can add the most value and what to expect technically.
What support and resources are available for building and scaling the Data Science team?
Why ask this? Clarifies the level of autonomy and backing you will have as you grow the function.
How does the company measure the commercial impact of its AI and risk intelligence products?
Why ask this? Shows your interest in aligning technical work with business outcomes.
What opportunities exist for experimenting with new technologies or approaches within the team?
Why ask this? Assesses the company's openness to innovation and your ability to drive technical direction.
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