Sr Data Scientist

INSPYR Solutions•Fort Worth, TX

1d•Hybrid

About The Position

We are seeking a highly skilled Sr Data Scientist with a Master's or PhD degree and at least 5 years of experience in a quantitative discipline. The ideal candidate will have strong Python proficiency, hands-on experience building Generative AI applications, and a deep understanding of ML/AI pipeline development and productionization. This role involves working with cutting-edge AI technologies, including LLMs and Agentic AI, and taking ML models from prototype to production. The position is a hybrid role in Fort Worth, TX, for a 6+ month contract.

Requirements

Master or PhD degree with 5 years of experience in a 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
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
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
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.

Nice To Haves

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
Microsoft Dynamics
Prompt Engineering
Proficiency in SQL and working with data
Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)

Responsibilities

Build Gen AI applications, including prompt engineering, classifiers, knowledge bases, RAG solutions, and using LLMs as judges.
Develop and productionize ML/AI pipelines, including model deployment, orchestration, monitoring, and optimization.
Apply statistical and machine learning techniques to solve complex problems.
Effectively communicate findings and insights to stakeholders at all levels.
Employ feature engineering techniques to improve model representation.
Collaborate effectively within a diverse team environment.
Take ML models from prototype to production, utilizing Python and Azure ML.
Containerize models as needed.
Optimize code, debug systems, and perform system integration.
Manage the end-to-end ML lifecycle, including deployment and monitoring.
Work with existing codebases, improving them, and building new ones from scratch.