Senior Full Stack Data Scientist

Relocation to Limassol, Cyprus

At Finom, we’re on a mission to transform the financial landscape for small and medium businesses (SMEs) across Europe. We’re all about innovation, putting our customers first, and making data-driven decisions. We’re building something special - a financial platform that simplifies finance management, eliminates routine tasks and makes life easier for our customers. As we expand, we’re looking for a Senior Machine Learning Engineer to join our Data Science & Machine Learning team and help us scale our efforts through data-driven insights and advanced machine-learning models.

What You Will Be Doing

• Anomaly Detection: Prepare and operationalize (deploy) MVPs for anomaly detection tasks in production.

• Graph & Entity Modeling: Improve the graph engine and refine entity connection logic to better define customer clusters and supply chains.

• Risk Logic: Enhance transaction categorization logic to maximize value and impact for both fraud detection and fraud prevention.

• Overall Focus: Bridge research and production through strong MLOps practices, specializing in risk management systems.

Who You Are

• Experienced Machine Learning Engineer or Full-stack Data Scientist with a solid track record in delivering production-grade ML solutions - 4-5 years of experience

• Proficient in Python and SQL-based programming

• Skilled in working with cloud-based data platforms such as Databricks

• Experienced in deploying machine learning models and API services (e.g., FastAPI) in production environments

• Strong understanding of system architecture and ability to design scalable ML solutions

• Analytical and critical thinker with a proactive, results-driven mindset

• Comfortable working in fast-paced, start-up environments with minimal supervision

• Educational background in mathematics, engineering, economics, or computer science

• Fluent in English, capable of working in an international environment

Hiring Process:

• 📞 HR Interview (30 minutes) – An initial conversation to learn more about your experience, motivation, and expectations.

• 🧠 Technical Interview (ML/DS/SQL) (1.5 hours) – A deep-dive into your foundational knowledge and practical experience across Machine Learning, Data Science, and SQL.

• 🧠 Technical Interview (ML System Design) (1 hour) – A focused discussion on designing and scaling Machine Learning systems.

• 📊 Final Interview (60 minutes) – A discussion with Hiring Manager and Head of Machine Learning and Data Science where you’ll present your assignment and walk through your decisions.

What You Will Get In Return

• Make a genuine impact on the product. Join our upward trajectory, and grow with us. We provide the resources and opportunities for continuous personal and professional development, empowering you to make a genuine impact on our evolving product.

• Work in the EU. Embark on this exciting journey with us and enjoy the flexibility of traveling and working remotely or in a hybrid model across Europe.

• Become a stock options holder. Unlock your inner entrepreneur and align your aspirations with ours through our Stock Options Program. This exciting opportunity is available to every team member, from junior team members to our founders.

• Receive unwavering support and care. Finom stands by you at every step, embodying our commitment to your well-being and success reflected in our modern, friendly, and eco-conscious corporate culture. We offer constant support and care to ensure your Finom experience is successful and fulfilling.

• Work & Swim program. Immerse yourself in our exclusive Work & Swim Program. Spend one month in a comfortable corporate apartment in enchanting Cyprus. It's the ideal opportunity to strike the perfect work-life balance while enjoying breathtaking Mediterranean views.

• Equal Opportunity Statement . At Finom, we're an equal opportunity employer and value diversity at our company. We embrace diversity and invite applications from all walks of life. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, disability status, or other applicable legally protected characteristics.