Role Overview:

We are seeking a Data Scientist with strong expertise in Python, SQL, and Machine Learning, and a working background in Generative AI, Retrieval-Augmented Generation (RAG), and Multi-Agent Frameworks. The ideal candidate will work on developing predictive and generative AI models that enhance cargo pricing, forecasting, routing optimization, and intelligent automation across the airline logistics ecosystem.

Key Responsibilities:

• Build, train, and deploy machine learning and deep learning models for forecasting, optimization, and decision support.
• Design and implement Generative AI applications such as chatbots, knowledge assistants, and intelligent document retrieval systems using RAG pipelines.
• Develop and orchestrate multi-agent systems for automating complex cargo processes (pricing, scheduling, customer insights, etc.).
• Leverage statistical modeling and data mining to uncover actionable insights from large-scale cargo, operations, and route datasets.
• Collaborate with cross-functional teams (engineering, product, and domain experts) to translate business challenges into AI-driven solutions.
• Perform data cleaning, feature engineering, and pipeline automation for model deployment and monitoring.
• Continuously explore new LLM, agentic AI, and MLOps tools for faster experimentation and production scaling.

Required Skills & Qualifications.

• Bachelor’s or Master’s from degree in Computer Science, Data Science, Statistics, or related field.
• 3+ years of professional experience in data science or applied machine learning.
• Strong proficiency in Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow).
• Solid command of SQL for querying and managing large datasets.
• Strong foundation in Statistics, Probability, and Linear Algebra.
• Hands-on experience with NLP frameworks (spaCy, Hugging Face Transformers, LangChain, etc.).
• Practical experience with Generative AI, RAG pipelines, LLM fine-tuning, and AI Agents (e.g., LangChain, LlamaIndex, OpenAI APIs).
• Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps tools (Docker, MLflow, FastAPI, etc.) is a plus.
• Excellent problem-solving, analytical thinking, and communication skills.

Preferred Skills.

• Experience in airline, logistics, or transportation data.
• Knowledge of optimization algorithms for pricing, scheduling, and route generation.
• Exposure to data visualization tools (Power BI, Tableau, Plotly).
• Experience integrating LLMs (GPT, Claude, Gemini, etc.) via APIs.
• Understanding of MLOps tools (MLflow, Kubeflow, Airflow, or Azure ML).