Senior Data Scientist (GTM)

Intercom
Full-timeData engineeringDublin, Ireland · Remote within Ireland
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At a glance

Employment type
Full-time
Workplace
Remote

Technologies & skills

Primary technologies

Other technical skills

Secondary technologies

What you'll be doing

Senior Data Scientist role on the Research, Analytics & Data Science (RAD) team at Fin (part of Salesforce), focused on designing, evaluating, and shipping AI-powered internal tools for GTM use cases. High-ownership, end-to-end role with impact on business outcomes and close collaboration with GTM teams.

  • Design, evaluate, and ship AI-powered internal tools for GTM use cases
  • Own the full lifecycle from problem definition and data modeling to building production-ready tools
  • Write Python backends and React frontends
  • Rapidly prototype with users and productionize quickly
  • Instrument tools for adoption and measurable business outcomes
  • Document playbooks and run enablement sessions
  • Help leaders operationalize new tooling across teams

Key requirements

Must-have

  • Proven track record of applied data science with measurable GTM impact
  • LLM/ML application experience (e.g., RAG, prompt and tool design, vector search, evals)
  • Excellent SQL skills
  • Fluency in Python or R
  • Experience with orchestration tools (e.g., DBT, Airflow)
  • Strong communication and ability to translate complex data concepts for non-technical stakeholders
  • Collaborative product mindset and comfort working with Sales and Success teams

Role signals

Technical focus
data science, AI-powered internal tools, end-to-end development
Hands-on vs management
Hands-on

Full job description

Fin, now part of Salesforce, is 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, giving modern support teams one single system.

Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI.

Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce.

The Opportunity

The Research, Analytics & Data Science (RAD) team turns insight into action. We uncover customer, product, and business insights and translate them into tools and decision systems embedded directly into GTM workflows.

AI has unlocked an entirely new generation of internal tools for our GTM teams. We’re evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations.

The RAD team partners closely with GTM Systems to define problems, solutions, and measure impact - from prototype to production.

This is a high-ownership role for someone who thrives in ambiguity, is energized by solving complex real-world problems, and is motivated by seeing their work translate into tangible business impact.

What You’ll Do

  • Design, evaluate, and ship AI-powered internal tools for GTM use cases - including account research & summaries, next-best-action recommendations, renewal propensity, pipeline risk detection, QBR/autobrief generation, and post-call summarization & follow-ups.

  • Work end-to-end: Own the full lifecycle, from problem definition and data modeling to building production-ready tools, including writing Python backends and React frontends.

  • Prototype fast, ship to learn: Rapidly build with users, then productionize quickly to iterate and deliver impact.

  • Instrument for adoption and outcomes: Define success through real usage and measurable business impact (e.g., improved win rate, conversion, expansion).

  • Evangelize and enable: Document playbooks, run enablement sessions, and help leaders operationalize new tooling across teams.

What You Bring

  • Proven track record of applied data science with measurable GTM impact - you’ve shipped models or tools that moved metrics like conversion, cycle time, or retention.

  • LLM/ML application experience - familiarity with RAG, prompt and tool design, vector search, evals and have leveraged AI for development.

  • Excellent SQL skills and fluency in Python or R, with experience applying analytical and statistical methods to business problems.

  • Experience with orchestration tools (e.g., DBT, Airflow) for deploying reliable data workflows.

  • Strong communication and empathy - ability to translate complex data concepts for non-technical stakeholders.

  • Collaborativeproduct mindset- comfort working closely with Sales and Success teams to turn ambiguity into clear deliverables.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers. Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.

**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.

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Interview prep pack

Grounded in this listing. Use it to prepare examples before you apply.

Your interview focus

Based on this listing, the Senior Data Scientist (GTM) role at Fin (now part of Salesforce) focuses on designing, building, and deploying AI-powered internal tools for go-to-market (GTM) teams, with a strong emphasis on measurable business impact and end-to-end ownership.

  • GTM business impact·High
  • LLM/ML application·High
  • End-to-end product development·High
  • Stakeholder communication·Medium

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

  1. Review and Select GTM Impact Stories

    0–7 min

    Identify 1-2 strong examples where your data science work drove measurable GTM outcomes.

  2. Refresh LLM/ML and Orchestration Knowledge

    7–14 min

    Study recent projects or literature on LLMs, RAG, prompt engineering, and orchestration tools relevant to the stack.

  3. Prepare End-to-End Project Narratives

    14–20 min

    Outline your approach to full lifecycle tool development, including technical and stakeholder aspects.

  4. Practice Communication and Enablement Examples

    20–25 min

    Rehearse explaining technical concepts and adoption strategies for non-technical audiences.

  5. Draft Role-Specific Questions

    25–30 min

    Write down and refine questions to ask the interviewers about team priorities, processes, and challenges.

Likely questions

, 6 items

Priority reflects how strongly this topic is emphasised in the job listing, not whether it will be asked.

Talking points

, 5 items
  • Demonstrating GTM Impact with Data Science

    Prepare examples where your work directly improved business metrics such as conversion, retention, or sales cycle time.

  • Building and Deploying AI/ML Solutions

    Showcase your experience with LLMs, RAG, prompt engineering, and deploying models or tools into production environments.

  • End-to-End Tool Development

    Be ready to discuss projects where you owned the lifecycle from problem definition to production, including backend (Python), frontend (React), and orchestration (Airflow, dbt).

  • Translating Data Insights for Non-Technical Stakeholders

    Highlight your ability to communicate complex data concepts and drive adoption among Sales and Success teams.

  • Rapid Prototyping and Iterative Delivery

    Prepare to discuss how you quickly built prototypes, gathered user feedback, and iterated to deliver impactful solutions.

What to research

, 4 items
  • Review GTM Metrics and Use Cases

    Understand key GTM metrics (conversion, retention, pipeline risk) and how data science can impact them.

  • Brush Up on LLM/ML Techniques

    Refresh your knowledge of LLMs, RAG, prompt engineering, and vector search as applied to business tools.

  • Practice End-to-End Tool Development

    Be ready to discuss projects involving Python, SQL, React, and orchestration tools like Airflow or dbt.

  • Prepare Communication Examples

    Gather stories where you translated technical insights for non-technical stakeholders and drove tool adoption.

Questions to ask

, 6 items
  1. What are the most critical GTM workflows or metrics the RAD team is currently focused on improving?

    Why ask this? Clarifies business priorities and where your work will have the most impact.

  2. How does the team balance rapid prototyping with ensuring production-quality standards?

    Why ask this? Shows your interest in both speed and reliability in development.

  3. What is the typical collaboration model between RAD, GTM Systems, and Sales/Sales Success teams?

    Why ask this? Helps you understand cross-functional dynamics and expectations.

  4. How is the adoption and business impact of new tools measured and communicated to stakeholders?

    Why ask this? Demonstrates your focus on outcomes and continuous improvement.

  5. What are the biggest challenges the team faces when operationalizing new AI-powered tools?

    Why ask this? Gives insight into potential obstacles and areas where you can add value.

  6. What opportunities exist for contributing to the broader AI strategy within Salesforce and Agentforce?

    Why ask this? Shows your interest in growth and alignment with company vision.

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Apply NowApply before: 23 Oct 2026