Data Scientist (Pricing)
Emerging Travel Group • Serbia • Kazakhstan
No Relocation
Posted: August 20, 2026
Job Description
- Engage with the business objectives behind key tasks: pricing for B2B/B2C, forecasting and optimization of financial and operational metrics, incident prioritization, and improving customer journey efficiency (revenue growth, cost savings, business impact).
- Drive ML projects end-to-end: from problem definition and formalization to modeling, piloting, and presenting results.
- Collaborate with data engineers to collect the necessary datasets and assess implementation feasibility.
- Work with analysts on A/B test design: defining metrics, splits, and interpreting results.
- Develop models (classic ML and DL, time series, uplift modeling), conduct error analysis and performance evaluation.
- Prepare models and code for transfer to production infrastructure (deployment and releases handled by the technical team).
- Take ownership of model quality, monitor key metrics, and collaborate with the team on degradation issues and improvement plans.
- 3+ years of experience as a Data Scientist.
- Proven experience with end-to-end ML projects (ability to oversee the entire process).
- Strong knowledge of classical machine learning techniques (feature engineering, classification, regression, boosting, etc.).
- Hands-on experience with uplift modeling and time series tasks (with real business applications).
- Experience working with business stakeholders and understanding optimization problems: pricing, B2C, LTV, retention, AB testing, and more.
- Proficient in Python for DS/ML (writing clean, readable code for models and experiments).
- Confident SQL user (able to build datasets, write joins, and perform data analysis).
- Nice to have: experience with MLflow/DVC, pipelines (Airflow or similar), anomaly detection/anti-fraud, deep learning (PyTorch/TensorFlow), and model monitoring.
Additional Content
- Engage with the business objectives behind key tasks: pricing for B2B/B2C, forecasting and optimization of financial and operational metrics, incident prioritization, and improving customer journey efficiency (revenue growth, cost savings, business impact).
- Drive ML projects end-to-end: from problem definition and formalization to modeling, piloting, and presenting results.
- Collaborate with data engineers to collect the necessary datasets and assess implementation feasibility.
- Work with analysts on A/B test design: defining metrics, splits, and interpreting results.
- Develop models (classic ML and DL, time series, uplift modeling), conduct error analysis and performance evaluation.
- Prepare models and code for transfer to production infrastructure (deployment and releases handled by the technical team).
- Take ownership of model quality, monitor key metrics, and collaborate with the team on degradation issues and improvement plans.
- 3+ years of experience as a Data Scientist.
- Proven experience with end-to-end ML projects (ability to oversee the entire process).
- Strong knowledge of classical machine learning techniques (feature engineering, classification, regression, boosting, etc.).
- Hands-on experience with uplift modeling and time series tasks (with real business applications).
- Experience working with business stakeholders and understanding optimization problems: pricing, B2C, LTV, retention, AB testing, and more.
- Proficient in Python for DS/ML (writing clean, readable code for models and experiments).
- Confident SQL user (able to build datasets, write joins, and perform data analysis).
- Nice to have: experience with MLflow/DVC, pipelines (Airflow or similar), anomaly detection/anti-fraud, deep learning (PyTorch/TensorFlow), and model monitoring.