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Join a team where data science fuels smarter e-commerce and marketing automation. You'll take end-to-end ownership of machine learning solutions — from concept to production — shaping customer experiences and driving measurable value across a fast-evolving product ecosystem.
Job Responsibility:
Owning full model lifecycle: from research, experimentation and prototyping to deployment and monitoring
Building and optimizing machine learning models using Python e.g., customer lifetime value models, AI modules that support the recommendation engines and the use of a customer data platform
Designing data pipelines and integrating ML solutions into production (search personalization, clickstream analysis, email triggers)
Improving and maintaining existing models to ensure performance, scalability, and robustness in production
Collaborating closely with engineering, product and business teams to turn complex data into actionable product features
Upholding high development standards by writing clean, maintainable code, conducting code reviews, and embracing DevOps practices like testing and CI/CD
Contributing to the continuous improvement of the team by mentoring junior colleagues and bringing new perspectives to modeling and methodology discussions
Requirements:
Experience in end-to-end data science projects (preferably in eCommerce, SaaS, MarTech space), around 5 years of experience
Strong background in Python. Experience deploying models in production environments
Experience with Azure infrastructure, including Kubernetes and Azure Pipelines
Solid understanding of statistics, modeling, and software engineering practices
Analytical mindset with a passion for practical impact, not just research
Excellent English and communication skills
Strong communication skills, with the ability to explain data-driven insights to diverse audiences
An ability to take charge of your own projects as well as close collaboration with others