Working in partnership with business teams to identify opportunities for improvement, gather and analyze information and data, developing solutions & driving innovation
Apply knowledge of statistics, machine learning, programming, and data modeling to recognize patterns, identify opportunities, evaluate business opportunities, and deliver high impact models
Effectively structure communication of insights from work streams and deliver clear and professional presentations to the team/team leaders/managers/stakeholders
Formulate and develop end-to-end project pipelines to deploy scalable solutions on company platforms
Execute solutions to business problems using data analysis, machine learning and optimization tools
Mentoring junior resources on data science skills
Research on latest machine learning models and share the knowledge across the team
This position is offered on local terms and conditions. Expatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded. This position is for United Airlines Business Services Pvt. Ltd - a wholly owned subsidiary of United Airlines Inc.
Qualifications
What’s needed to succeed (Minimum Qualifications)
Bachelor's degree in engineering, Technology, Computer Science, Statistics, Operations Research, Applied Mathematics, Economics
Full-time 2+ years relevant work experience in analytics/data science
Strong foundation in machine learning, statistics, and applied mathematics, with hands-on experience solving real-world business problems using data and AI.
Strong proficiency in Python and SQL, with experience working with large and complex datasets.
Experience across the end-to-end machine learning lifecycle, from data preparation and model development to evaluation and production deployment.
Hands-on experience with classification, regression, ensemble methods, gradient boosting, and clustering.
Hands-on experience building AI solutions using Generative AI and foundation models, including prompt engineering, embeddings, vector search, RAG, and AI agents.
Ability to translate business problems into AI/ML solutions and define appropriate success metrics.
Strong analytical, problem-solving, and communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
Ability to work effectively as an individual contributor and collaborate with cross-functional teams
What will help you propel from the pack (Preferred Qualifications)
Master's degree/ MTech in Data Science, Business Analytics, Engineering, Technology, Computer Science, Statistics, Operations Research, Applied Mathematics, Economics
Hands-on experience with deep learning and neural networks, including frameworks such as PyTorch or TensorFlow.
Experience in one or more AI domains such as Computer Vision, Generative AI, Large Language Models (LLMs), or Natural Language Processing.
Experience building production-grade AI/ML systems, including model serving, inference, monitoring, performance optimization, and model lifecycle management.
Experience with AWS and cloud-based ML platforms, particularly SageMaker, S3, Redshift, Athena, and data lake architectures.
Experience with MLOps and ML engineering practices, including CI/CD, model versioning, experiment tracking, automated pipelines, and monitoring.
Experience working with distributed data processing and large-scale machine learning.