Sr Data Scientist

About the role

ML/AI team supporting Contact Centers and Digital Customer Experience. Collaborative, supportive, and high-performing culture with strong focus on quality, innovation, scalability, and measurable revenue impact.

Responsibilities

• Support the Service Recovery Modernization initiative
• Take ownership of data preparation, data pipelines, design, test, and deployment of ML and Gen AI applications
• Collaborate closely with data scientists, data engineers, and product partners
• Accelerate delivery of scalable, production-ready AI solutions

Minimum Qualifications

• Master or PhD degree with 5+ years of experience in quantitative discipline (e.g., Data Science, Machine Learning Engineer, Computer Science, Applied Mathematics, Statistics, etc.)
• Python proficiency (production-grade coding, modularization, testing, performance tuning)
• Hands-on experience with building Gen AI applications – prompt engineering, classifiers, knowledge bases, RAG solutions, LLMs as judges, etc.
• Hands-on experience with ML/AI pipeline development and productionization (model deployment, orchestration, monitoring, and optimization)
• Depth of knowledge in statistical and machine learning techniques

Preferred Qualifications

• Experience with Azure ML, Databricks
• Proficiency in SQL and working with data
• Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)
• Practical experience designing, building and deploying machine learning models
• Domain knowledge in the airline industry
• Experience working in a consulting role

Skills

• Ability to effectively communicate both verbally and written with all levels within the organization
• Demonstrated motivation and aptitude for logical analysis, problem identification, and problem solving
• Ability to view data from different angles to employ feature engineering techniques to better represent models
• Ability to work on a diverse team with diverse skillsets
• 5-7 years of experience required

Ideal Candidate Profile

• Has experience with LLMs and Agentic AI
• Has experience building customer facing Gen AI applications; awareness on guardrails, privacy, cybersecurity concerns
• Has proven experience taking ML models from prototype to production with Python and Azure ML; containerize where needed
• Demonstrated strong skills in code optimization, debugging, and system integration
• Understands end-to-end ML lifecycle, including deployment and monitoring
• Is comfortable working with existing codebases and improving them, as well as building new ones from scratch
• Clear communication and effective collaboration

Team Structure

The resource will be embedded within the team and support the Service Recovery Modernization initiative. Will collaborate with several team members. Collaborative, supportive, and high-performing culture. Strong focus on quality, innovation, scalability, and measurable revenue impact.