Senior Data Scientist-Gen AI/RAG

YO AI Labs

Houston (TX)

On-site

USD 140,000 - 210,000

Full time

5 days ago
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Job summary

YO AI Labs in Houston seeks a Senior Data Scientist with deep ML/DS background and hands-on GenAI experience (LLMs, RAGs, agentic workflows) to build and deploy enterprise-scale AI solutions. You will interact with customers, translate business problems into data science deliverables, and collaborate with product and engineering teams to deliver measurable results.

The role requires strong Python/R, ML frameworks, data modeling, and experience deploying models to production, with a focus on

Qualifications

  • 5–7 years of relevant experience.
  • Hands-on agentic AI production experience — LangGraph, LangChain, MCP, tool calling.
  • RAG implementation depth — vector databases, hybrid retrieval, reranking, knowledge graphs.
  • AWS Bedrock experience (Azure OpenAI or Vertex AI acceptable as alternative).
  • Strong traditional ML/DS background — classification, regression, forecasting, anomaly detection, feature engineering, model evaluation.
  • 12+ months continuous, recent hands-on GenAI/LLM work.
  • Production deployment experience.

Responsibilities

  • Develop and implement ML algorithms to solve complex business problems.
  • Analyze large datasets to generate insights and inform decision-making processes.
  • Collaborate with product managers and engineers to integrate data science solutions into enterprise products.
  • Communicate findings and recommendations effectively to technical and non-technical stakeholders.
  • Stay current with the latest advancements in data science and machine learning technologies.

Skills

GenAI experience
Customer interaction
Analytical thinking
Communication

Tools

Python
R
TensorFlow
PyTorch
Scikit-learn
Tableau
Power BI
Hadoop
Spark
SQL

Job description

Job Description
Role : Senior Data Scientist-Gen AI/RAG
Domain : Information technology (IT)
Job Type: Full Time
Location : USA - Houston
Experience: 7 - 15 Years
Job Summary:

Looking for a Senior Data Scientist with a strong traditional ML/DS background and hands-on experience in GenAI (LLMs, RAGs, Agentic workflows), we need someone with practical implementation experience and the ability to interact confidently with customers. The selected candidate will leverage advanced analytical techniques and machine learning methods to derive actionable insights from complex datasets.

Key Responsibilities:
  • Develop and implement machine learning algorithms to solve complex business problems.
  • Analyze large datasets to generate insights and inform decision-making processes.
  • Collaborate with product managers and engineers to integrate data science solutions into enterprise products.
  • Communicate findings and recommendations effectively to technical and non-technical stakeholders.
  • Stay current with the latest advancements in data science and machine learning technologies.
Skills and Tools Required:
  • Strong proficiency in programming languages such as Python or R.
  • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Solid understanding of statistical analysis techniques and data modeling.
  • Proficiency in data visualization tools (e.g., Tableau, Power BI).
  • Familiarity with big data technologies (e.g., Hadoop, Spark).
  • Ability to work with databases and query large datasets using SQL.
  • Strong problem-solving skills and the ability to think critically.
Must Haves:
  • A 5-to-7-years of Relevant experience is needed.
  • Hands-on Agentic AI production experience — LangGraph, LangChain, MCP, tool calling.
  • RAG implementation depth — vector databases, hybrid retrieval, reranking, knowledge graphs.
  • AWS Bedrock experience (Azure OpenAI or Vertex AI only acceptable as an alternate, not a substitute for GenAI cloud exposure generally).
  • Strong traditional ML/DS background — classification, regression, forecasting, anomaly detection, feature engineering, model evaluation.
  • 12+ months continuous, recent hands-on GenAI/LLM work.
  • Production deployment experience
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