Job overview and responsibilities:
The Analytics and Innovation (Ai) team at United Airlines works to innovate, transform, and solve complex business problems resulting in significant and measurable enterprise impact through the application of deep cross-functional business expertise and advanced analytics. We work with business and technology partners across the enterprise (e.g. Airport Operations, Contact Centers, Network Planning, Revenue Management, Digital Products, Human Resources, etc.) to influence strategic decisions, enterprise strategy, business process, and to help connect the dots across the enterprise. We aim to be an organization with whom and within everyone loves to work!
Data Scientists within Ai partner with business and technology leaders across the company to deploy AI & ML powered solutions to support and automate business processes. The team works closely with other teams in digital technology with complementing skills and capabilities. The key objectives are to drive incremental revenue, boost customer engagement and to automate manual processes by leveraging state-of-the-art ML techniques. Data Scientists contribute in developing smart and innovative solutions across many of United’s departments.
- Working on projects in conjunction with business teams to identify opportunities for improvement, gather and analyze information and data, develop improvements and innovations
- Apply knowledge of statistics, machine learning, programming, and data modeling to recognize patterns, identify opportunities, evaluate business opportunities, and deliver valuable insights
- Effectively structure communication of insights from work streams and deliver clear and professional presentations to the team/team leaders/managers/stakeholders
- Scope, size and plan DS project roadmaps with clear milestones, metrics and identify potential derailment factors. Drive end-to-end execution from incubation to production.
- Deliver high quality AI/ML solutions and maintain proper documentation to foster seamless workflows and code-reusability principles.
- Performing regular technical coordination/reviews with stake holders and ensuring timely reporting and escalations if any
- Propose and develop innovative solution approaches based on scientific research or empirical studies
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):
- BTech/Bachelor’s degree in Engineering, Technology, Computer Science, Statistics, Operations Research, Applied Mathematics, Economics
- Full time 4-7 years relevant work experience in analytics/data science
- Proficiency with mathematics and statistical analysis with significant hands-on experience in AI / Data Science.
- Proficiency in Programming Languages (Python), SQL, Excel and other Microsoft Office products
- Knowledge in exploratory analysis, predictive modeling, prescriptive modeling, strong understanding of machine learning algorithms like Regression, Bagging (Decision Trees, RF), Boosting (XGBoost, GBM), Clustering (KMeans), Deep learning, NLP and Computer Vision.
- Hands on experience of working in Deep Learning Models and related frameworks like TensorFlow, Keras, PyTorch etc.
- Sound understanding in AWS services including Sagemaker, Redshift, Athena, S3 & AWS data lake.
- Ability to bridge business context with technical details and explain and discuss mathematical and machine learning technicalities to a business audience
- Ability to work collaboratively with a variety of business, data science and technical stakeholders.
What will help you propel from the pack (Preferred Qualifications):
- MTech/Master’s degree in Data Science, Business Analytics, Engineering, Technology, Computer Science, Statistics, Operations Research, Applied Mathematics, Economics
- Previous airline business experience
- Experience in developing & deploying the end-to-end data science pipeline into production.