- Home
- Jobs
- Data engineering
- Senior Finance Data Scientist, Existing Business
Senior Finance Data Scientist, Existing Business
On this page
TechJobs.ie Job Insights
At a glance
- Employment type
- Full-time
- Workplace
- Remote
- Category
- Data engineering
What you'll be doing
As a Senior Finance Data Scientist, Existing Business at Fin, you will architect and maintain predictive models and data pipelines to forecast revenue, model customer value, and provide actionable financial insights. The role blends technical rigor with financial intuition, supporting executive decision-making and business strategy.
- Build and maintain predictive models for usage-based revenue, renewals, and expansion
- Develop propensity models to identify expansion opportunities and churn risks
- Design and maintain curated finance datasets
- Define and iterate on LTV frameworks linking product engagement to financial outcomes
- Build automated forecasting workflows for financial planning
- Own end-to-end data pipelines transforming raw data into model-ready datasets
- Write and optimize production-quality SQL and Python for large-scale datasets
- Ensure data integrity and consistency across predictive systems
Key requirements
Must-have
- 3+ years in Data Science, Strategic Finance, or Revenue Analytics with SaaS or usage-based business models
- High proficiency in Python (pandas, scikit-learn)
- Expert-level SQL
- Experience building scalable data pipelines and analytical tools
- Strong understanding of NRR, LTV, Churn, and product usage-revenue relationships
Nice-to-have
- Experience with forecasting libraries (e.g., Prophet, Nixtla)
Experience: 3+ years in Data Science, Strategic Finance, or Revenue Analytics with a focus on SaaS or usage-based business models
Role signals
- Technical focus
- Data Science, Financial Modeling, Data Engineering
- Architecture / system design
- Indicated in the listing
- Hands-on vs management
- Hands-on
Similar jobs
Full job description
Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences.
Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams.
Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers.
What's the opportunity?
As a Senior Finance Data Scientist, Existing Business, you will be the architect of the systems that predict Fin's revenue future. You will move beyond static reporting to build production-grade forecasting models that translate complex customer behaviors into financial signals.
You will work on high-impact, open-ended problems, such as predicting expansion propensity and modeling long-term customer LTV. This role requires a hybrid of financial intuition and technical rigor: the ability to navigate raw data warehouses and the strategic mindset to explain the "why" behind the numbers to our leadership team.
The Impact You Will Have
-
Own and Evolve the Revenue Engine: Build and maintain predictive models for usage-based revenue, renewals, and expansion that outperform traditional linear forecasts.
-
Unlock Predictive Insights: Develop propensity models to identify expansion opportunities and churn risks before they materialize in the ledger.
-
Architect Finance Data: Design and maintain curated datasets that serve as the single source of truth.
-
Model Customer Value: Define and iterate on our LTV frameworks, providing a clear linkage between product engagement and long-term financial outcomes.
Drive Scalability: Build automated, code-based forecasting workflows that increase the speed, reliability, and granularity of our financial planning.
What will I be doing?
Predictive Modeling and Forecasting Systems
-
Build and own probabilistic and time-series models that project ARR performance across renewals and usage-based motions.
-
Incorporate behavioral signals, such as product adoption, seat utilization, and feature engagement, into expansion propensity and LTV frameworks.
-
Design models that account for cohort dynamics, seasonality, and product-led growth (PLG) signals.
-
Evaluate model performance through backtesting and iteration, ensuring our "financial weather forecast" is constantly improving.
Data and Analytical Infrastructure
-
Own the end-to-end data pipeline for finance, transforming raw product usage and billing data into curated, model-ready datasets in our data warehouse.
-
Write and optimize production-quality SQL and Python to work with large-scale datasets and automate complex FP&A workflows.
-
Ensure data integrity and consistency across all predictive systems and executive dashboards.
-
Contribute to the long-term data strategy for how Fin tracks and predicts Existing Business health.
Analytical Problem Solving
-
Translate ambiguous business questions (e.g., "Which usage signals best predict a 2x expansion?") into structured data science projects.
-
Connect ARR outcomes to underlying drivers like product adoption, customer health scores, and GTM activity.
-
Perform scenario modeling and sensitivity analysis to help the business understand the range of possible outcomes for NRR.
Business Partnership & Communication
-
Partner with Sales, Product, and Data Engineering to align our financial models with actual customer behavior and product roadmaps.
-
Translate complex statistical outputs into clear, decision-oriented narratives for the CFO and executive leadership.
-
Build executive-ready materials, including predictive dashboards and strategic presentations.
What skills do I need?
-
3+ years in Data Science, Strategic Finance, or Revenue Analytics, with a deep focus on SaaS or usage-based business models.
-
Advanced Technical Skills: High proficiency in Python (pandas, scikit-learn) and Expert-level SQL. Experience with forecasting libraries (e.g., Prophet, Nixtla) is a major plus.
-
System Design Mindset: Experience building scalable data pipelines and production-grade analytical tools, not just one-off spreadsheets.
-
SaaS Mastery: Strong understanding of NRR, LTV, Churn, and the relationship between product usage and revenue.
-
Communication: Ability to translate technical work into business insight and influence stakeholders through data-driven storytelling.
-
Business Judgment: A focus on accuracy and a "Product Sense" that allows you to see the human behavior behind the data points.
-
AI-Augmented Productivity: Proficiency in leveraging AI-native development tools (e.g. Cursor, Claude Code) to accelerate the development of data pipelines, model prototyping, and code documentation.
What Success Looks Like
-
Automated forecasting models that are more accurate, granular, and less manual than previous iterations.
-
A clear Propensity Score integrated into our planning that successfully predicts customer expansion and contraction.
-
Scalable, code-based workflows that reduce the time-to-insight for the Existing Business team.
High confidence from leadership in our ability to predict the financial impact of changing customer usage patterns.
Benefits
We are a well-treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us!
-
Competitive salary and equity in a fast-growing start-up
-
We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
-
Regular compensation reviews - we reward great work!
-
Pension scheme & match up to 4%
-
Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
-
Flexible paid time off policy
-
Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
-
If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too
-
MacBooks are our standard, but we also offer Windows for certain roles when needed.
#LI-Hybrid
**Policies **
Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.
We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values.
Fin values diversity and is committed to a policy of Equal Employment Opportunity. Fin will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.
Interview prep pack
Grounded in this listing. Use it to prepare examples before you apply.
Your interview focus
Based on this listing, the Senior Finance Data Scientist, Existing Business role at Fin focuses on building and maintaining advanced predictive models and data pipelines to forecast revenue and customer value in a SaaS environment. The position emphasizes technical rigor, financial acumen, and the ability to translate complex data into actionable insights for executive leadership.
- Technical Depth in Predictive Modeling·High
- Data Engineering and Pipeline Ownership·High
- Financial Acumen in SaaS Metrics·High
- Business Communication·Medium
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review SaaS Financial Modeling Concepts
0–7 minRefresh your understanding of NRR, LTV, churn, and their drivers in SaaS and usage-based models.
Prepare Case Studies on Predictive Modeling
7–15 minSelect 1-2 examples from your experience building forecasting or propensity models, focusing on business impact and technical approach.
Brush Up on SQL and Python Skills
15–22 minPractice writing and optimizing queries and scripts for large-scale data transformation and analysis.
Research Fin's Product and Data Ecosystem
22–27 minUnderstand Fin's AI Customer Agent, its integration with Intercom, and the types of product usage data available.
Draft Questions for the Interviewers
27–30 minPrepare thoughtful questions about team collaboration, technical challenges, and success metrics.
Talking points
, 5 itemsBuilding Probabilistic and Time-Series Forecasting Models
You will need to demonstrate experience designing and iterating on models that predict revenue, renewals, and expansion in SaaS or usage-based businesses.
Developing and Maintaining Scalable Data Pipelines
The role requires end-to-end ownership of transforming raw product and billing data into curated, model-ready datasets using SQL and Python.
Linking Product Usage to Financial Outcomes
You should be able to explain how product engagement metrics drive financial KPIs like LTV, NRR, and churn, and how you have modeled these relationships.
Communicating Analytical Insights to Executives
Prepare examples of translating complex statistical outputs into clear, actionable narratives and dashboards for non-technical stakeholders.
Scenario Modeling and Sensitivity Analysis
Showcase your ability to perform scenario analysis to help leadership understand the range of possible financial outcomes.
What to research
, 4 itemsFin's Product Suite and Customer Journey
Review Fin's AI Customer Agent and its integration with Intercom to understand the product signals available for modeling.
SaaS Financial Metrics and Modeling Techniques
Refresh your knowledge of NRR, LTV, churn, and how these are modeled in usage-based SaaS businesses.
Advanced SQL and Python for Data Engineering
Prepare to discuss and demonstrate your expertise in writing production-quality SQL and Python for large-scale data transformation and analysis.
Forecasting Libraries and Tools
Familiarize yourself with forecasting libraries such as Prophet or Nixtla, as experience with these is considered a plus.
Questions to ask
, 6 itemsHow does the finance data science team collaborate with Sales, Product, and Data Engineering to align models with business strategy?
Why ask this? To understand cross-functional workflows and expectations for stakeholder engagement.
What are the biggest challenges currently faced in forecasting revenue and customer expansion at Fin?
Why ask this? To identify key pain points and areas where your expertise can add value.
How is model performance evaluated and iterated upon in production?
Why ask this? To clarify expectations for model monitoring, backtesting, and continuous improvement.
What is the current data stack and what opportunities exist for improving data infrastructure?
Why ask this? To assess the technical environment and potential for innovation.
How are insights from predictive models communicated to executive leadership and incorporated into strategic decisions?
Why ask this? To gauge the impact of your work and the importance of communication skills.
What does success look like in this role after the first 6-12 months?
Why ask this? To set clear expectations for performance and growth.
Register now to upload your CV
Create a free account, save a PDF or Word CV, and quick apply on roles that take applications here.
