At a Glance
- Tasks: Lead the design and deployment of advanced data science models to drive commercial impact.
- Company: Global tech and professional services firm expanding analytics in Financial Services.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Mentor a growing team and shape commercial strategies in a dynamic environment.
- Why this job: Make a real difference in financial services through impactful data-driven decisions.
- Qualifications: 8-10 years in Data Science with strong Python and SQL skills.
The predicted salary is between 80000 - 100000 £ per year.
A global technology and professional services organisation with a long-established Financial Services practice is expanding its advanced analytics capability in Ireland. They are appointing a Lead Data Scientist to anchor and scale their Marketing & Distribution Analytics function across Asset Management, Life Insurance, and Retirement solutions.
This is a technical leadership role, not a purely individual contributor position. The successful candidate will define how predictive analytics, segmentation, and propensity modelling are designed, governed, and operationalised across the business. You will also mentor a small but growing team of data scientists and act as a trusted partner to senior commercial leaders. The focus is clear: analytics that drives commercial action, not reporting for its own sake.
The Lead Data Scientist will own end-to-end delivery of marketing and distribution analytics within the Financial Services practice. The emphasis is on measurable commercial impact, including:
- Improving conversion through advanced customer segmentation
- Driving distribution decisions via propensity and predictive models
- Quantifying customer lifetime value across products and channels
- Turning insight into clear commercial trade-offs and decisions
The role operates at the intersection of data science, commercial strategy, and regulated model governance, requiring both technical depth and the ability to communicate clearly in a Financial Services environment subject to model-risk scrutiny.
Key Responsibilities
- Analytical Leadership
- Lead the design, development, and deployment of advanced data science models across segmentation, propensity scoring, predictive analytics, and lifetime value modelling
- Translate ambiguous commercial questions into structured, solvable analytical problems
- Own the Marketing & Distribution Analytics roadmap, prioritising work based on commercial impact and stakeholder needs
- Ensure outputs are decision-oriented rather than purely descriptive analytics
- Technical Delivery
- Build and deploy production-grade models using Python and SQL
- Operate across cloud environments including Amazon Web Services (AWS) and Microsoft Azure (Azure)
- Develop clear, decision-focused reporting layers using Microsoft Power BI, ensuring insight is accessible to non-technical stakeholders
- Integrate intent and signal-based data sources (e.g. 6sense, Bombora, or equivalents) into marketing and distribution models
- Establish and enforce standards for model documentation, reproducibility, validation, and version control
- Stakeholder Partnership
- Partner with senior leaders across Marketing, Distribution, Product, and Commercial functions
- Communicate complex analytical outcomes in a clear, business-focused manner for executive audiences
- Provide credible challenge to assumptions and shape commercial strategy through evidence-based insight
- Act as the primary technical voice in planning and decision forums
- Team Leadership
- Mentor and develop a small team of data scientists
- Set technical standards and ensure consistency in modelling approaches and outputs
- Review analytical work for technical robustness, commercial alignment, and governance compliance
- Contribute to hiring, onboarding, and capability development within the analytics function
- Governance & Controls
- Ensure all models comply with internal model risk management, audit, and regulatory requirements
- Maintain alignment with data privacy, governance, and ethical AI standards
- Support model validation processes in collaboration with risk and compliance teams
- Ensure transparency and explainability of all deployed models in line with Financial Services expectations
Essential Experience
- 8–10 years’ experience in Data Science, Advanced Analytics, or Marketing Analytics
- Significant exposure to Financial Services environments
- Proven track record of delivering production-grade ML/AI models that have driven measurable commercial outcomes
- Strong hands-on expertise in Python and SQL across full model lifecycle
- Experience deploying solutions across AWS and Azure
- Practical use of Power BI for decision support (not just visual reporting)
- Familiarity with intent/signal platforms such as 6sense, Bombora, or equivalents
- Experience mentoring or leading junior data scientists and establishing technical standards
Desirable Experience
- Direct experience in Asset Management, Life Insurance, or Retirement sectors
- Exposure to model risk governance, validation, and regulatory oversight frameworks
- Experience working with MarTech, CRM, CDP, or distribution platform data ecosystems
- Postgraduate qualification in a quantitative discipline (Statistics, Computer Science, Mathematics, Engineering, or related field)
Data Scientist in Letterkenny employer: Vertor Consulting Group Ltd
Join a leading global technology and professional services organisation that prioritises innovation and measurable impact in the Financial Services sector. With a hybrid work model in Ireland, you will benefit from a collaborative work culture that fosters employee growth through mentorship and technical leadership opportunities. The company is committed to driving commercial success through advanced analytics while ensuring compliance with regulatory standards, making it an excellent employer for those seeking meaningful and rewarding careers.
Contact Details:
Vertor Consulting Group Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Letterkenny
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those that demonstrate your ability to drive commercial impact. This will make you stand out when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the business side of things. Be ready to discuss how your analytics can lead to measurable outcomes in financial services.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Scientist in Letterkenny
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Lead Data Scientist. Highlight your experience in data science, especially in Financial Services, and showcase any relevant projects that demonstrate your ability to drive commercial outcomes.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've led analytics projects and mentored teams, and don’t forget to mention your technical skills in Python, SQL, and cloud environments.
Showcase Your Analytical Leadership:In your application, emphasise your experience in leading analytical projects. We want to see how you've translated complex business questions into actionable insights and how you've driven measurable impact through your work.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture!
How to prepare for a job interview at Vertor Consulting Group Ltd
✨Know Your Data Science Inside Out
Make sure you’re well-versed in the technical aspects of data science, especially Python and SQL. Be ready to discuss your experience with building production-grade models and how they’ve driven measurable outcomes in previous roles.
✨Understand the Financial Services Landscape
Familiarise yourself with the specific challenges and opportunities within the Financial Services sector, particularly in Asset Management, Life Insurance, and Retirement. This will help you articulate how your skills can directly impact their business goals.
✨Prepare for Stakeholder Engagement
Since this role involves partnering with senior leaders, practice explaining complex analytical concepts in a clear, business-focused manner. Think about examples where you've successfully communicated insights to non-technical stakeholders.
✨Showcase Your Leadership Skills
Be prepared to discuss your experience mentoring junior data scientists and how you’ve set technical standards in previous roles. Highlight any instances where you’ve contributed to team development or improved modelling approaches.
