Data Scientist (Hybrid)

Job Description

We are looking for a talented and impact-driven Data Scientist to join our growing analytics team. In this role, you will take end-to-end ownership of data science projects, from design to deployment, and play a key role in transforming our airline's retail and revenue management capabilities through cutting-edge machine learning and optimization techniques.

This is a unique opportunity to work at the intersection of technology, analytics, and commercial strategy in a fast-evolving industry.

Key Responsibilities:

Lead end-to-end execution and deployment of data science solutions in production environments.
Collaborate with integration engineers to manage live environment testing and deployment.
Develop and implement analytical models, with a strong focus on dynamic pricing and optimization.
Contribute to core projects in dynamic bundling and product recommendation systems.
Take a key role in revenue management initiatives, aligned with Modern Airline Retailing strategies.
Support innovation by contributing to emerging areas such as chatbots, visual/video content generation, and Agentic AI when required.

Required Qualifications:

Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, or a related field.
Strong knowledge of machine learning, predictive analytics, and optimization techniques.
Hands-on experience with Python and common data science libraries (e.g., Pandas, Scikit-learn, TensorFlow, PyTorch).
Proven experience in deploying data science models in production.
Familiarity with version control tools (e.g., Git) and ML Ops practices.
Strong collaboration skills to work with cross-functional teams (engineering, business, product).
Experience in airline or travel industry is a plus.

Ready to take off with us? Apply now and be part of the journey.

Amaris Consulting is committed to promoting diversity within its workforce and to creating an inclusive work environment. We review applications from all qualified individuals regardless of gender, sexual orientation, race, ethnicity, beliefs, age, marital status, disability, or any other characteristic. Special consideration will be given to candidates with disabilities.

Data Scientist (Hybrid)

Key Skills

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