Responsibilities
Work with subject matter experts from airlines to identify opportunities for leveraging data
to deliver insights and actionable prediction of customer behavior and operations
performance.
Assess the effectiveness and accuracy of recent data sources, data gathering and
forecasting techniques.
Develop custom data models and algorithms to apply to data sets and run proof of concept
studies.
Leverage existing Statistical and Machine Learning tools to enhance in-house algorithms.
Collaborate with software engineers to implement and test production quality code for
AI/ML models.
Develop processes and tools to monitor and analyze data accuracy and models’
performance.
Demonstrate software to customers and perform value proving benchmarks. Calibrate
software for customer needs and train customer for using and maintaining software.
Resolve customer complaints with software and respond to suggestions for
enhancements.
Required Qualifications
Advanced Degree in Statistics, Operations Research, Computer Science, Mathematics, or
Machine Learning.
Proven ability to apply modeling and analytical skills to real-world problems.

Knowledge of machine learning techniques (clustering, decision tree learning, artificial
neural networks, etc.) and statistical concepts (regression, properties of distributions,
statistical tests, etc.).




Solid programming skills 2-3 languages out of R, SQL, Python, TensorFlow, PySpark,
Java, JavaScript or C++.
Absolutely must have: graduate school level knowledge of Revenue Management models
and algorithms.
Experience (minimum 4 out of 7) with deployment of machine learning and statistical
models on a cloud:
1. MLOps within the enterprise CI/CD process for ML models – 2 years
2. Experience deploying ML APIs in production environments in GCP using GKE – 2 years
3. Experience in using GCP Vertex AI for ML and BigQuery – 1 year
4. Knowledge in Terraform and Containers technologies – 2 years
5. Experience writing data processing jobs using GCP Dataflow and Dataproc – 2 years
6. Experience setting up ML model monitoring and autoscaling for ML prediction jobs – 1 year
7. Understanding of machine learning concepts to scale ML across different services by
leveraging Feature Store, Artifacts Registry and Analytics Hub – 1 year

Desirable Qualifications
Familiarity with airline, hospitality or retailing industries and decision support systems
employed there.
Experience developing customer choice models, price elasticity estimation and market
potential estimation.
Understanding of airline distribution, pricing, revenue management, NDC and Offer/Order
Management concepts.

📌 Data Scientist (Delhi)
🏢 TENARAI TECHNOLOGIES PRIVATE
📍 Delhi