Data Scientist

🕒 June 10

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Paystone

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2013

📣 Marketing

📦 Logistics

🏥 Healthcare

💰 Venture Round on 2021-07

Marketing • Logistics • Healthcare

Paystone is a comprehensive integrated platform that offers businesses robust solutions for payment processing, gift cards, loyalty programs, and marketing automation. The company provides various tools, including payment terminals, e-commerce capabilities, virtual terminals, and POS systems, designed to streamline business operations and enhance customer engagement. Paystone's services aim to boost sales, increase customer visits, and improve customer loyalty by combining real-time reporting and analytics with flexible payment options. With a strong presence in North America, Paystone supports over 35,000 businesses, offering them opportunities to grow with secure, automated, and efficient solutions.

📋 Description

• Partner with Product and BI to turn business goals into well-scoped ML problems with clear success criteria and guardrails. • Build and productionize models for segmentation, churn, LTV, and recommendations. • Design evaluation frameworks including offline benchmarks and online feedback loops to ensure models are measured, not assumed. • Collaborate with Engineering on production design considerations like latency, payload structure, fallbacks, and failure modes. • Monitor model performance over time, detect drift, and own retraining and iteration cycles. • Use product telemetry and user feedback to drive continuous model and feature improvements. • Work alongside AI coding agents to accelerate development while maintaining human oversight. • Communicate results, trade-offs, and recommendations clearly across technical and non-technical teams.

🎯 Requirements

• 5+ years as a Data Scientist, Applied Scientist, or ML Engineer • Strong SQL and Python skills with production ML experience • Experience with churn, segmentation, LTV, or recommender systems • Comfortable working with production systems and APIs • Familiar with AI coding tools and agentic workflows • Strong communicator who can simplify technical concepts. • Nice to Have: Experience in loyalty, CRM, or retail analytics, LLM or AI agent experience, Building internal tools or ML infrastructure, French/English bilingual.

🏖️ Benefits

• Flexibility: People-first approach focused on outcomes, not location or hours. • Innovation: Work at the intersection of machine learning, product thinking, and AI-assisted development. • Collaboration: Partner closely with Product, Engineering, and BI in a fast-moving, supportive environment.