Staff Data Scientist, GTM Engineering

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Company Overview

A leading global fintech organization is building a unified payments and financial platform that enables businesses worldwide to manage accounts, payments, spend management, treasury, and embedded finance through integrated solutions. With a global workforce spanning multiple international offices, the company is focused on driving innovation in financial technology and empowering businesses to operate seamlessly across borders.

The organization values individuals with strong ownership, curiosity, and a builder mindset. Team members are encouraged to leverage AI-driven technologies, solve complex challenges, and contribute to high-impact initiatives while collaborating with talented professionals across the globe.

The GTM Data Science team is a collaborative group of analytics and data science professionals dedicated to driving commercial success through data-driven insights. The team partners closely with Product, Growth, and Commercial functions to accelerate revenue growth, optimize operational efficiency, and establish scalable data foundations for future business expansion.

The organization is seeking a Staff Data Scientist, GTM Engineering to serve as a technical leader within the GTM Data Science team. This role will involve partnering cross-functionally to develop advanced solutions for go-to-market challenges, including revenue forecasting, causal inference, and AI-driven commercial insights.

This position offers the opportunity to conduct exploratory analysis, translate sophisticated models into actionable business recommendations, and help shape the organization’s data science operating model.

Key Responsibilities

• Partner with Product, Growth, and Commercial teams to design and implement data science solutions that improve revenue generation and commercial outcomes.
• Lead exploratory analyses to identify revenue opportunities, uncover trends, and operationalize insights into scalable workflows.
• Develop and maintain revenue forecasting models and performance metrics, including pipeline health, conversion and retention analysis, and scenario planning.
• Apply advanced causal inference methodologies, such as Difference-in-Differences (DiD), Synthetic Control, and DoubleML, to evaluate business impact and guide strategic decisions.
• Design and deploy AI-enabled solutions across the sales and customer lifecycle, including initiatives related to sales effectiveness, customer retention, and expansion.
• Present technical findings and recommendations to both technical and non-technical stakeholders, including executive leadership.
• Mentor and coach junior data scientists while providing technical leadership on cross-functional, high-impact projects.

Required Qualifications

• Minimum of 8 years of industry experience with an advanced degree (MS or PhD) in a quantitative discipline such as Statistics, Computer Science, Engineering, Economics, or a related field.
• Demonstrated experience mentoring or leading data science or analytics teams.
• Strong analytical and problem-solving capabilities with the ability to translate business challenges into impactful analytical initiatives.
• Excellent communication skills with experience influencing strategic decisions and presenting technical insights to diverse audiences.
• Proficiency in SQL and Python and/or R.
• Hands-on experience with revenue forecasting and causal inference methodologies.
• Experience applying data science within technology, financial services, or other high-growth environments.

Preferred Qualifications

• Experience with Databricks or similar cloud-based data platforms and data warehouses.
• Familiarity with Hex or other notebook-based analytical tools.
• Knowledge of B2B business models, CRM systems, sales pipelines, and Revenue Operations (RevOps) data.
• Experience mentoring teams within startup, fintech, or other fast-paced environments.

Disclaimer

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