Data Scientist - Marketing and Distribution Analytics

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AI Summary

We are seeking a Data Scientist to apply AI/ML and advanced analytics to improve customer targeting, campaign performance, and distribution effectiveness in regulated, data-rich environments. The role involves developing and applying AI/ML models, creating analytical solutions, and delivering insights to support business stakeholders. The ideal candidate will have experience in Data Science, Marketing Analytics, and cloud-based analytics platforms.

Key Highlights
Develop and apply AI/ML models for customer segmentation, propensity modelling, predictive analytics, and lead scoring.
Build, deploy, and maintain analytical solutions using AWS and Azure services.
Collaborate with marketing, distribution, sales, technology, and data engineering teams to improve targeting, engagement, and conversion outcomes.
Key Responsibilities
Develop and apply AI/ML models for customer segmentation, propensity modelling, predictive analytics, and lead scoring.
Build, deploy, and maintain analytical solutions using AWS and Azure services.
Create scalable analytical datasets and reusable code using Python and SQL.
Deliver insights and dashboards in Power BI to support: Audience and segment analysis Campaign and distribution performance Interpretation of model outputs for business stakeholders
Collaborate with marketing, distribution, sales, technology, and data engineering teams to improve targeting, engagement, and conversion outcomes.
Communicate analytical findings clearly to both technical and non-technical audiences.
Technical Skills Required
Python SQL Machine learning techniques Power BI Databricks SageMaker Azure Machine Learning
Benefits & Perks
Annual Bonus Scheme
Contributory Pension
Private Medical Insurance
Life Assurance & Long-Term Disability
Employee Assistance Programme
22 days annual leave + 10 public holidays
Relocation package
Continuous Learning & Development
Access to extensive training & certification resources
Lunch & Learn sessions
Additional perks including company discounts, on-site parking, and bike-to-work scheme
Nice to Have
Experience in Asset Management, Insurance, Retirement, or advisor/intermediary-led distribution models.
Exposure to cloud-based analytics and model deployment practices in AWS and Azure environments.

Job Description


My client is seeking a Data Scientist with experience in Marketing and Distribution Analytics within Financial Services/ Asset Management. The role focuses on applying AI/ML and advanced analytics to improve customer targeting, campaign performance, and distribution effectiveness in regulated, data-rich environments.


Key Responsibilities


  • Develop and apply AI/ML models for customer segmentation, propensity modelling, predictive analytics, and lead scoring.
  • Build, deploy, and maintain analytical solutions using AWS and Azure services, including SageMaker, Azure Machine Learning, and Databricks.
  • Create scalable analytical datasets and reusable code using Python and SQL.
  • Deliver insights and dashboards in Power BI to support:
  • Audience and segment analysis
  • Campaign and distribution performance
  • Interpretation of model outputs for business stakeholders
  • Collaborate with marketing, distribution, sales, technology, and data engineering teams to improve targeting, engagement, and conversion outcomes.
  • Communicate analytical findings clearly to both technical and non-technical audiences.


Skills & Experience


  • 5+ years experience in Data Science, Marketing Analytics, or a related analytical role, with good exposure to Financial Services and cloud‑based analytics platforms.
  • Strong hands-on experience with Python, SQL, and machine learning techniques.
  • Experience with Power BI and data visualisation for business decision-making.
  • Familiarity with AI-driven lead scoring and intent platforms such as 6sense, Bombora, or similar tools.
  • Understanding of Financial Services data, including customer, advisor, product, and transactional datasets.
  • Knowledge of data governance, privacy, and model risk considerations within regulated environments.
  • Ability to balance technical depth with commercial awareness and stakeholder engagement.



Preferred Experience


  • Experience in Asset Management, Insurance, Retirement, or advisor/intermediary-led distribution models.
  • Exposure to cloud-based analytics and model deployment practices in AWS and Azure environments.


Salary dependent on candidate experience. Benefits: Annual Bonus Scheme. Contributory Pension. Private Medical Insurance. Life Assurance & Long-Term Disability. Employee Assistance Programme. 22 days annual leave + 10 public holidays. Relocation package. Continuous Learning & Development. Access to extensive training & certification resources. Lunch & Learn sessions. Additional perks including company discounts, on-site parking, and bike-to-work scheme


Based in Letterkenny, Co. Donegal. Hybrid (2-3 days onsite per week). Candidates must be eligible to work in Ireland/EU.


For more information, please contact David Coyle at 01 635 1748 or email david@methodius.com


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