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Data Scientist

CloudiousUnited States🇺🇸United StatesPosted 14 Aug 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Top 3 Mandatory Skills and Experience:

-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

Minimum Qualifications Education & Prior Job Experience

  • 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 Education & Prior Job Experience

  • 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, Licenses & Certifications

  • 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

Nice to Have Skills:

- Microsoft Dynamics
- Prompt Engineering
- Proficiency in SQL and working with data

-Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)

Skills

SQL
MLflow
Machine Learning
Azure
Databricks
Python

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