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
Join a global AI leader as a Data Scientist focusing on ML models and AI-powered risk intelligence solutions. This hands-on role involves building machine learning models, data pipelines, and scalable analytics to deliver predictive insights across various risk domains. Collaborate with Product, Engineering, and Data teams to solve complex problems and improve processes.
- 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 technical solutions
- Deploy, monitor, and optimise machine learning models in production
Key requirements
Must-have
- 3-5 years of experience in Data Science or Machine Learning
- Strong Python skills
- Strong SQL, database, and data engineering fundamentals
Experience: 3-5 years
Role signals
- Technical focus
- Data engineering
- Hands-on vs management
- Hands-on
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Full job description
Data Scientist – ML & AI-Powered Risk Intelligence!
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Join a global AI leader transforming risk intelligence
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Build machine learning models with real business impact
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Work on innovative AI solutions from anywhere in Dublin
An exciting opportunity has opened for a Data Scientist to join a global technology organisation developing AI-powered risk intelligence solutions. 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.
Working closely with Product, Engineering, and Data teams across the business, you’ll solve complex problems, develop practical AI solutions, and continuously improve models and processes through an iterative, data-driven approach.
This is an excellent opportunity to join a growing data science team where your work will directly contribute to product innovation, smarter decision-making, and next-generation risk intelligence solutions used by global organisations.
Why This Role Stands Out
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Work on AI and machine learning solutions used by global enterprise clients
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Own projects from data preparation and modelling through to production deployment
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Join a growing team with strong visibility and impact
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Collaborate with international Product and Technology teams
What You’ll Be Doing
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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 technical solutions
-
Deploy, monitor, and optimise machine learning models in production
What You Bring
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3-5 years of experience in Data Science or Machine Learning with strong Python skills
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Strong SQL, database, and data engineering fundamentals
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
Interested in building AI solutions that solve complex business problems and deliver real-world impact?
Contact Serena Akbib on +353 1 960 9972 or send your CV to [email protected].
Interview prep pack
Grounded in this listing. Use it to prepare examples before you apply.
Your interview focus
Based on this listing, the role of Data Scientist focuses on building machine learning models and data pipelines to deliver predictive insights in risk intelligence.
- Machine Learning Model Development·High
- Data Pipeline Management·High
- Predictive Analytics·High
- Collaboration with Cross-Functional Teams·High
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review Job Requirements
0–5 minGo through the job listing and insights to align your experience with the role's expectations.
Prepare STAR Examples
5–15 minDraft STAR responses for key experiences related to machine learning and data analysis.
Research Relevant Technologies
15–20 minSpend time learning about the tools and technologies mentioned in the listing.
Formulate Questions to Ask
20–25 minPrepare insightful questions to ask the interviewer about the team and projects.
Talking points
, 4 itemsMachine Learning Models
Prepare examples of models you've built, focusing on the impact they had on business decisions.
Data Pipeline Creation
Discuss your experience in building and maintaining data pipelines, emphasizing efficiency and scalability.
Predictive Analytics
Be ready to explain how you've used data analysis to develop predictive models and the results achieved.
Collaboration with Teams
Share experiences where you worked with product and engineering teams to solve complex problems.
What to research
, 3 itemsReview Machine Learning Frameworks
Familiarize yourself with popular frameworks like TensorFlow or PyTorch that may be relevant to the role.
Understand Risk Intelligence Applications
Research how AI and machine learning are applied in risk intelligence across various sectors.
Explore Data Pipeline Tools
Look into tools and technologies used for building data pipelines, such as Apache Airflow or AWS Glue.
Questions to ask
, 4 itemsWhat types of machine learning models are currently being used in your projects?
Why ask this? To understand the technical landscape and expectations for the role.
How does the data science team collaborate with product and engineering teams?
Why ask this? To gauge the level of cross-functional collaboration and communication.
What are the biggest challenges the team is currently facing?
Why ask this? To identify potential obstacles and areas where you could contribute.
Can you describe the typical lifecycle of a machine learning project here?
Why ask this? To understand the workflow and expectations for project management.
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