Sr Data Scientist

• 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

• 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

• 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
• Proficient in Python
• Experience/knowledge on designing and implementing Gen AI applications- Hands-on experience with Machine Learning and AI pipeline build model deployment orchestration monitoring and optimization

• Microsoft Dynamics
• Prompt Engineering
• Proficiency in SQL and working with data
• Experience with ML lifecycle tools (e.g. MLflow CI/CD model monitoring)
• Describe a great candidate that you are looking for and what skills and experience they will have:
• 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.

• Comprehensive medical benefits
• Competitive pay
• 401(k) retirement plan
• and much more!

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