Apply advanced AI/ML methods to solve business and customer problems
Design, develop, and scale machine learning models and prototypes suitable for production integration
Partner with engineering, product, and business teams within Agile delivery environments
Take end-to-end ownership of models, ensuring performance, reliability, and continuous enhancement across their lifecycle
Contribute to full-cycle development, including feature engineering and production readiness
Review code, provide peer feedback, and maintain high engineering and quality standards
Build and maintain strong working relationships with internal stakeholders and external partners
Convert complex analytical outputs into clear, actionable insights for both technical and non-technical audiences
Decompose ambiguous business challenges into well-defined data science problem statements
Stay up to date with industry advancements in AI/ML and actively apply new knowledge
Collaborate with other data science teams to strengthen standards, practices, and culture
Produce and maintain comprehensive documentation for models, workflows, and processes to support transparency and knowledge sharing

5 years of practical experience delivering data science solutions in real-world business contexts
Strong programming skills in Python with a focus on clean, maintainable, and reusable code
Advanced SQL capabilities and hands-on experience working with large, unstructured, or inconsistent datasets
Solid foundation in mathematics, statistics, and machine learning methodologies
Proven experience deploying and maintaining machine learning models in production environments
Ability to translate complex business challenges into structured analytical problems
Strong communication skills, with the ability to clearly present insights to non-technical stakeholders
Business-oriented mindset with a clear understanding of how analytical outputs translate into value, trade-offs, and growth opportunities
Practical experience with Azure-based tools for model development, deployment, and lifecycle management
Continuous learning mindset with interest in emerging AI/ML techniques and technologies

Flexible hours and remote-first mode
Competitive compensation
Complete Hardware/Software setup – anything you need for work
Open-door culture, transparent communication, and top management at a handshake distance
Health insurance, vacation, sick leaves, holidays, paid maternity/paternity leave
Access to our learning & development center: workshops, webinars, training platform, and edutainment events
Virtual team buildings and social activities

Data Scientist

Key skills