Senior Data Science Engineer - Dynamic Pricing & Revenue

JobCubby; Hinoba-an; On-site; PHP 900,000 - 1,800,000; Full time

Benefits offered by this job

Learning opportunities

Flexible working model

Health benefits

Global exposure

Job summary

Amadeus is seeking a Senior Data Science Engineer to lead advanced modeling for dynamic pricing and revenue management in airline environments. You will build real-time optimization, manage large-scale data pipelines, and apply ML techniques to maximize revenue, collaborating across data science, engineering, and research teams.

Ideal candidates have 9–12 years in data science, strong Python/Java/Scala skills, and hands-on experience with PyTorch, TensorFlow, Kafka, SQL, and visualization tools

Qualifications

• 9–12 years in Data Science, ML or related roles.
• Strong programming in Python, Java, Scala, PySpark.
• Hands-on with ML frameworks: PyTorch, TensorFlow, Keras, XGBoost.
• Proficient in Big Data tech: Hadoop, Spark, Scala; streaming with Kafka.
• SQL, MongoDB; data viz with Tableau/Power BI.
• ETL pipelines; cloud familiarity (Azure); Databricks a plus.

Responsibilities

• Analyze specifications and define user requirements for software solutions.
• Design and develop technical solutions; perform feasibility studies and propose workarounds.
• Develop software in line with Amadeus standards.
• Data engineering: acquire data sets and design data pipelines; ensure data quality and governance.
• Train and calibrate ML models; define KPIs and monitor performance.
• Industrialize prototypes into production and perform tests.
• Support customers by interpreting model results and providing expertise.

Skills

Python

Java

Scala

PySpark

ML frameworks

Big Data

Kafka

SQL

MongoDB

Tableau

Power BI

ETL pipelines

Azure

Databricks

Tools

Hadoop

Spark

Databricks

Kafka

Azure

Tableau

Power BI

MongoDB

SQL

PyTorch

TensorFlow

Keras

XGBoost

Job description

Amadeus is seeking a Senior Data Science Engineer to lead advanced modeling for dynamic pricing and revenue management in airline environments. You will build real-time optimization, manage large-scale data pipelines, and apply ML techniques to maximize revenue, collaborating across data science, engineering, and research teams.

Ideal candidates have 9–12 years in data science, strong Python/Java/Scala skills, and hands-on experience with PyTorch, TensorFlow, Kafka, SQL, and visualization tools