Senior Machine Learning Researcher (m/f/d)

About Buynomics: 

“What will customers buy?” is the crucial question underlying all commercial decisions in all companies. Buynomics has developed Virtual Shopper technology, which answers this question 100x faster and more precisely than every other solution. This will end the common practice of gut feeling. Our goal is to enable companies to make data-driven, transparent, and customer-centric commercial decisions. For that, we build the operating system for commercial decisions that provides companies with a single source of truth to answer all their market-facing questions including pricing, product offers, and promotions. 

Buynomics is the next-generation SaaS company in pricing and product optimization. It employs large-scale simulation technologies to digitize customers and predict their purchase behavior - in any environment. Our clients use Buynomics to make data-driven decisions about their current and new products, overall portfolio structure, pricing, promotions, trade terms, and more!

Job Summary:

We are looking for a Senior Machine Learning Researcher with a strong background in mathematical modeling and algorithm development. In this role, you will play a key part in designing, implementing, and optimizing advanced models and algorithms that drive our core technology. You will collaborate with a high-impact Machine Learning team to solve complex business problems and deliver innovative solutions that support commercial decision-making at scale.

Responsibilities:

• Own the development and implementation of mathematical models and algorithms to address business challenges and enhance our Virtual Shopper technology
• Design, prototype, and optimize algorithms for large-scale data analysis, simulation, and prediction
• Collaborate with cross-functional teams to translate business requirements into robust modeling solutions
• Mentor and support junior team members in best practices for modeling, coding, and algorithmic thinking
• Evaluate and integrate new modeling techniques and technologies to continuously improve our analytical capabilities
• Contribute to the documentation, testing, and maintenance of our modeling and algorithmic codebase

Requirements:

• 6+ years of experience in data science, machine learning, or a related field, with a focus on mathematical modeling and algorithm development
• Advanced proficiency in Python and its scientific and ML libraries (e.g., NumPy, PyTorch, Pandas)
• Master’s or PhD in Mathematics, Economics, Statistics, Computer Science, Physics, Engineering, or a related quantitative field
• Experience in developing, validating, and deploying mathematical models and algorithms in production environments
• Solid understanding of statistical methods, optimization, and simulation techniques
• Experience with version control, code review, and collaborative software development
• Excellent problem-solving, communication and teamwork skills

What we offer:

• A vibrant, international, and diverse work environment
• Flexible work options: remote within the EU with occasional visits to our Cologne HQ or Barcelona office or a hybrid setup in one of these locations
• A dedicated learning budget to support your professional growth and development
• Local language lessons (Germany and Spain)
• Health and fitness benefits (Germany and Spain)
• Personal and professional growth opportunities
• Regular company events

To ensure a smooth and efficient process and that no applications are overlooked, please apply directly to the role. While we'd love to respond to everyone who reaches out, applying ensures that your application is properly tracked and considered.

Buynomics is proud to be an equal opportunity employer. This means that we don’t discriminate based on race or ethnic origin, color, the language(s) you speak, where you (or your parents) are from, or whether or not you consider yourself to have a disability. Neither will your age, gender, gender identity, sexual orientation, religion, beliefs, or political opinions play a part in your application with us. We’re a diverse team in so many ways, and we love it that way.