Data Scientist
First seen by Alion on Aug 28, 2026.
Role summary:
You will own the end-to-end delivery of ML- and data-driven capabilities for clientsturning business needs into production-grade data pipelines, deployed models (recommendation / NLP / GenAI), and measurable outcomes. This is a builder + owner role: you will be accountable for technical delivery, operational reliability, and proactive stakeholder expectation management.
Total Experience: 8-9 years
Core responsibilities:
- Own the end-to-end delivery of production-grade ML systems for recommendations, NLP, and personalization.
- Take full ownership of scalable data pipelines. Architect, build, and operate robust ETL/ELT systems.
- Establish and enforce data architecture standards. Design scalable storage patterns for analytics and ML.
- Drive MLOps as a discipline. Build and institutionalize CI/CD-aligned ML workflows.
- Deliver production-ready systems. Expose model and data capabilities through versioned APIs.
- Own stakeholder outcomes and client success.
Must-have Experience:
- End-to-end ownership of at least one production ML deliverable.
- Hands-on delivery of scalable data pipelines.
- Production software practices: testing, CI/CD, API design, monitoring.
- Client-facing delivery and stakeholder management.
- Practical data-lake experience.
Tech Stack & Qualifications:
- Bachelors degree in computer science, Data Analytics, Engineering, or a related discipline.
- Strong grasp of core data engineering principles, including data lake architectures, columnar storage formats, ETL/ELT frameworks, and BI ecosystems.
- Ability to operate effectively in independent and collaborative environments.
- Strong written and verbal communication skills.
- Sharp critical thinking and structured problem-solving abilities.
- High degree of ownership and adaptability.
Skills
Machine Learning, Data Science, NLP, Generative AI, ETL, Data Scientist