Senior Data Scientist

About the Project

This position is offered through hubQuest and delivered for one of our strategic client-partners. It is a long-term collaboration, where you will become part of a dedicated analytical hub built and operated by hubQuest.

You will work in an embedded model — closely integrated with the client’s global structures — while remaining part of hubQuest’s growing international data community. This is not a short-term contract or project-based engagement, but a stable, long-term partnership focused on building and evolving advanced AI-driven solutions.

We’re reimagining how global brands plan and execute promotions by building scalable, AI-driven advisory solutions powered by advanced Machine Learning and Operations Research models, robust cloud infrastructure, and intuitive front-end interfaces.

Our solutions directly drive measurable revenue growth for global brands. As part of this journey, you’ll make a tangible impact through the models, insights, and innovations you create.

You’ll join a diverse, multicultural, fully remote team of Data Scientists, Backend Engineers, and Frontend Developers working together to shape the future of promotional intelligence.

Your Role

As a Senior Data Scientist, you will take ownership of developing and productionizing advanced machine learning models and services. Your work will go far beyond notebooks — you’ll help design stable, reproducible, and automated ML pipelines that operate reliably in production environments.

You will:

• Lead full-cycle data science initiatives — from requirements gathering and exploratory analysis to deployment, monitoring, and iterative improvement.

• Design scalable data and ML pipelines, build reusable components, improve model accuracy, and contribute to documentation and PR reviews.

• Collaborate closely with Data Engineering, MLOps, Product, and Frontend teams to deploy and maintain solutions on Azure.

• Work effectively within complex development environments (Dev Containers, pre-commit frameworks, virtual machines).

• Drive client-facing delivery, including production rollouts, UAT, and model acceptance.

• Translate analytical results into clear business insights and communicate commercial impact (P&L, revenue implications).

• Provide training and post-deployment support.

• Apply optimization techniques to real-world promotional planning problems and build strong domain expertise.

• Guide 1–2 Data Scientists during deployments, coordinate features across multiple workstreams, and align timelines and expectations with internal and client stakeholders.

What You Bring

Core Expertise

• Advanced expertise in Machine Learning and Data Science, with the ability to design, validate, and productionize sophisticated models.

• Strong Python proficiency, including writing clean, modular, and production-ready code.

• Solid hands-on experience with Azure, including deploying and maintaining data/ML solutions in cloud environments.

• Basic familiarity with Deep Learning concepts and frameworks, with the ability to understand and apply them when needed.

• Working knowledge of SQL, sufficient to query, validate, and explore data independently.

• Good understanding of Git-based version control workflows, including collaborative development and pull request processes.

  
  

Experience & Skills

• 5+ years of experience in Data Science or ML Engineering with ownership of the production ML lifecycle.

• Strong analytical thinking and quantitative problem-solving skills (formal degrees welcome but not required).

• Hands-on experience with ML tools such as pandas, NumPy, SciPy, scikit-learn, and Matplotlib.

• Experience working with Azure-based solutions in production environments.

• Familiarity with CI/CD, MLOps concepts, Docker/Kubernetes, and model deployment strategies.

• Strong ability to reason about model behavior, edge cases, and failure modes.

• Fluent English (spoken and written) for global collaboration.

• Appreciation for diversity and the ability to thrive in a global, multicultural environment.

What Will Make You Successful

• Comfortable working under high-pressure deadlines and managing multiple priorities.

• Strong organizational habits — transparent workstreams, disciplined Jira updates, proactive risk communication.

• Thrives in a hybrid role combining technical execution, client interaction, and business understanding.

• Highly self-directed and proactive, able to take initiative with minimal supervision.

• Adaptable in rapidly changing technical and business contexts.

• Committed to continuous learning and professional growth.

Nice to Have

• Knowledge of deep learning frameworks.

• Practical SQL experience.

• Experience in Agile delivery environments.

• Experience with optimization solvers (e.g., Gurobi).

• Familiarity with data quality frameworks and validation strategies.

• Experience working in distributed teams across multiple time zones.

About hubQuest

hubQuest is a team of tech and data enthusiasts on a mission to bring together the best minds in IT and analytics. We build and operate long-term analytical hubs for our partners, enabling them to become truly data-driven organizations through cutting-edge AI and data solutions.

By joining us, you become part of a stable, growing international structure — not a temporary project team.

What We Offer

• Long-term cooperation within a stable strategic partnership

• Flexible working hours

• Remote or hybrid work model

• Private medical care and Multisport card

• Access to online learning platforms and certifications

• Global knowledge exchange

• A relaxed, non-corporate atmosphere with genuine respect for expertise and ownership

Please add to your CV the following clause:

"I hereby agree to the processing of my personal data included in my job offer by hubQuest spółka z ograniczoną odpowiedzialnością located in Warsaw for the purpose of the current recruitment process.”

If you want to be considered in the future recruitment processes please add the following statement:

"I also agree to the processing of my personal data for the purpose of future recruitment processes.”