Data Scientist

Flatpay; København; On-site; DKK 550,000 - 700,000; Full time

Benefits offered by this job

6 weeks paid vacation

Pension and health insurance

Flat structure with strong action-over

Company merch and social events

Job summary

Flatpay is seeking a Data Scientist to design, build, and productionize GenAI-powered products and pipelines that enable data-driven decisions across the organization.

You will work on customer-facing conversational AI, AI-driven document and media processing, and production deployment from ideation to scale, with a strong emphasis on applied ML, LLMs, and generative AI.

Qualifications

• 1–3 years of industry experience in Data Science, ML, AI Engineering, or a similar technical role.
• Hands-on experience building and maintaining customer-facing GenAI applications in production.
• Experience with multiple frontier/open-source LLM providers and understanding model trade-offs.

Responsibilities

• Design, build, and maintain production-grade GenAI applications and pipelines using Python and leading AI platforms.
• Develop AI-powered solutions including conversational AI, data enrichment, and multimodal processing systems.
• Write clean, well-tested production Python code with automated tests and monitoring.
• Build and maintain data and AI workflows in Databricks with pipelines, jobs, and model serving endpoints.
• Leverage cloud platforms (GCP, AWS, Azure) to provision and scale AI services.
• Integrate and optimize AI workflows with external platforms and providers.
• Collaborate with data engineers to ensure reliable data foundations for AI products.
• Drive projects from PoC to production deployment and ongoing optimization.

Skills

Python

Databricks

PySpark

Pandas

SQL

LLMs

GenAI

Testing

Production deployment

Tools

Transformers library

LLM SDKs

OpenAI API

Anthropic API

Google AI Platform

Job description

About The Job

You will join a growing AI team of 11 talented colleagues with a shared mission: transforming data and AI into measurable business value for Flatpay and our merchants.

As a Data Scientist, you will design, build, and productionize GenAI-powered products and pipelines that support business-critical decisions across the organization. A key area of focus will be customer-facing conversational AI, where creativity, strong product thinking, and a user-centered mindset are essential for developing cutting-edge solutions.

In addition, you will work on AI-driven document, image, and audio processing systems that power critical business processes and analytics. You'll collaborate closely with the broader AI team while also taking ownership of projects and driving them from ideation to production.

This role is ideal for someone who enjoys solving complex problems with modern AI technologies and seeing their work create real-world impact. You will have the opportunity to work across the entire AI product lifecycle - from data engineering and model development to deployment and user-facing applications - while maintaining a strong focus on applied machine learning, LLMs, and generative AI.

We are looking for someone who thrives in a fast-moving environment, takes ownership, and is comfortable engaging directly with stakeholders to pursue opportunities, align solutions with business needs, and continuously drive improvement.

What You’ll Do

• Design, build, and maintain production-grade GenAI applications and pipelines using Python, MLflow, Databricks, and leading AI platforms such as OpenAI, Anthropic, and Google.
• Develop AI-powered solutions including customer-facing conversational AI, LLM-driven data enrichment and analytics workflows, and audio, image, and multimodal processing systems for both internal and customer-facing products.
• Write clean, maintainable, and well-tested production python code, including automated tests, monitoring, guardrails, validation frameworks, and fail-safe mechanisms to ensure reliability, security, and robustness in AI systems.
• Build, orchestrate, and maintain data and AI workflows in Databricks, including pipelines, jobs, workflows, model serving endpoints, and custom applications deployed on the Databricks platform.
• Leverage cloud platforms such as GCP, AWS, and Azure to provision, deploy, and scale AI services, including LLMs.
• Integrate, optimize, and manage AI workflows that leverage external platforms and services, including tools such as ElevenLabs, Metabase, and other third-party providers.
• Collaborate closely with data engineers to ensure AI products are built on reliable, scalable, and well-governed data foundations.
• Drive projects from proof of concept through production deployment, monitoring, and ongoing optimization

Who You Are

• You have 1–3 years of industry experience in Data Science, Machine Learning, AI Engineering, or a similar technical role.
• You have hands‑on experience building and maintaining customer‑facing GenAI applications and pipelines in production and understand the importance of automated testing, monitoring, guardrails, and reliability in production AI systems.
• You have experience using LLMs from multiple state‑of‑the‑art providers of frontier and open‑source models, and you have a deep understanding of the strengths and trade‑offs of different frontier and open‑source models.
• You have experience building applications that leverage retrieval‑augmented generation (RAG), tool calling, agents, or other modern LLM architectures.
• You are comfortable developing solutions in Python and working with libraries such as Transformers and the SDKs of leading LLM Providers.
• You are comfortable working in Databricks or similar cloud‑based data and AI platforms, including building pipelines, workflows, model serving endpoints, and production deployments.
• You have strong PySpark, Pandas, and SQL skills and are comfortable working with large, structured datasets.
• You are comfortable taking ownership of projects, working independently, and collaborating directly with stakeholders across the business.

Why Flatpay

• Impact: Ship AI and data solutions that create real impact in one of Europe’s fastest-growing companies.
• Meaningful products: Build models that help merchants and colleagues make better decisions, act on insights, and improve workflows.
• Learning and growth: Develop across forecasting, production ML, data engineering, and AI in a supportive team.
• Flat structure: Flat structure and a strong action-over-process culture
• Competitive salary
• Vacation: 6 weeks paid
• Relaxed atmosphere with optional social events such as minigolf evenings, hackathons, and company parties in exciting off‑site locations.
• Co‑workers with a passion for data and AI, and a passion for sharing knowledge daily.
• Pension and health insurance, as well as almost unlimited company merch.

About Flatpay

Flatpay is not just another payment solution; we’re dedicated to innovating the market for payment solutions and financial services in the SME segment with our customer‑centric and transparent services.

We’ve grown into one of the fastest‑growing fintech companies out of the Nordics and Denmark’s fastest unicorn company. Today, we’re more than 2,000 colleagues across Europe, building products that make a real difference for our customers.

We’re ambitious, move fast, and like to challenge the status quo - but we also believe work should be fun. We celebrate wins, help each other out, and create an environment where people can do great work while genuinely enjoying the journey.

Established in 2022 in Copenhagen with a commitment to transparency, we’ve streamlined card payments to small and medium‑sized businesses. Our innovative pricing model eliminates hidden costs and fees, offering a simple flat rate for all cards with no monthly subscription for our point‑of‑sale and payment solutions.

Operating in Denmark, Finland, Germany, Italy, France, the United Kingdom, and the Netherlands, we’re more than just a service provider; we are your trusted business partner.

We continuously strive to stay ahead of the curve, adapting our solutions to meet our clients’ evolving needs. Ready to be part of something extraordinary?