Data Scientist

Full-time

Generative AI, Regression, Modeling, LLM

Role Overview

Key Responsibilities

• Design, develop, and deploy Machine Learning and AI models to solve business problems in the airline domain (e.g., pricing, demand forecasting, customer experience, operations).
• Build and implement advanced analytics solutions using NLP, deep learning, and Generative AI techniques.
• Develop AI-powered applications such as chatbots, recommendation systems, and intelligent automation tools.
• Work with large-scale structured and unstructured datasets to extract actionable insights.
• Collaborate with cross-functional teams including business, engineering, and product teams to deliver impactful solutions.
• Deploy scalable solutions using cloud platforms (AWS/GCP/Azure) and modern frameworks.
• Monitor model performance and continuously improve accuracy and efficiency.

Required Skills & Qualifications

• Strong experience in Machine Learning, Deep Learning, and AI techniques.
• Hands-on experience with NLP, LLMs, and/or Generative AI (RAG, chatbots, etc.).
• Proficiency in Python, SQL, and data processing tools (e.g., PySpark).
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Knowledge of model deployment frameworks (FastAPI, Flask, Docker).
• Experience working in the airline/travel domain (pricing, operations, customer analytics, etc.) is highly preferred.
• Strong problem-solving skills and ability to translate business problems into analytical solutions.

Preferred Qualifications

• Experience with real-time data processing and AI-driven automation.
• Familiarity with tools like LangChain, Snowflake, or similar modern data platforms.
• Prior experience working in global or cross-functional teams.
• It is our policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds.