Data Scientist – Pricing

About the role

Join Emerging Travel Group as a Data Scientist focused on pricing, forecasting and optimization of financial and operational metrics. You will drive end‑to‑end machine‑learning projects that impact revenue growth, cost savings and overall business performance.

Key responsibilities

• Define, model, pilot and present ML solutions for B2B/B2C pricing, incident prioritisation and customer‑journey efficiency.
• Collaborate with data engineers to gather datasets and assess feasibility of production deployment.
• Work with analysts on A/B test design, metric definition, split creation and result interpretation.
• Develop classic ML, deep‑learning, time‑series and uplift models; conduct error analysis and performance evaluation.
• Prepare code and models for hand‑off to the technical team for deployment and release.
• Own model quality, monitor key metrics, and address degradation with improvement plans.

Required profile

• 3+ years of experience as a Data Scientist with end‑to‑end ML project delivery.
• Strong knowledge of classical machine‑learning techniques, feature engineering, classification, regression and boosting.
• Hands‑on experience with uplift modelling and time‑series tasks in real business contexts.
• Proven ability to work with business stakeholders on pricing, LTV, retention and optimisation problems.

Required skills

• Python for data science and machine learning.
• SQL for data extraction and analysis.
• Experience with MLflow or DVC for model versioning.
• Familiarity with pipeline orchestration tools such as Airflow.
• Knowledge of deep‑learning frameworks like PyTorch or TensorFlow.

What we offer

• Fully flexible work schedule – focus on results, not clock‑in time.
• Choice of remote, office or hybrid work format.
• Support for professional development, internal training programs and external conference funding.
• Language‑learning support with group and individual lessons.
• Corporate travel discounts on hotels and services.
• MyTime Day Off – an extra day for personal well‑being or important matters.