We are looking for a Senior Data Scientist with strong hands-on experience across Traditional Machine Learning, Generative AI, LLMs, RAG, and Agentic AI.
The ideal candidate will have 5–7 years of relevant experience, recent and continuous hands-on GenAI experience, and a proven track record of deploying AI/ML solutions into production environments. Strong client-facing communication and consulting experience are essential, as the candidate will need to explain technical architecture, decisions, and trade-offs to both technical and non-technical stakeholders.
Position: Senior Data Scientist
Location: Houston, TX
Job Type: Full-Time
Interview: In-person interview required at the Santa Clara, CA office
Relocation: Relocation assistance is available for qualified candidates
Work Authorization: / / H-1B Transfer
Must-Have Skills & Experience
- 5–7 years of relevant Data Science / Machine Learning experience.
- Strong traditional Machine Learning/Data Science background, including:
- Classification
- Regression
- Forecasting
- Anomaly detection
- Feature engineering
- Model evaluation and optimization
- 12+ months of continuous and recent hands-on GenAI/LLM experience.
- Strong production experience with Agentic AI, including:
- LangGraph
- LangChain
- MCP
- Tool calling
- Agent orchestration
- Hands-on production Agentic AI experience is mandatory — candidates whose experience is limited to POCs, hackathons, certifications, or experimentation will not be considered.
- Strong depth in RAG implementations, including:
- Vector databases
- Hybrid retrieval
- Reranking
- Knowledge graphs
- Hands-on experience with AWS Bedrock.
- Azure OpenAI or Google Vertex AI can be considered as alternatives, but candidates must have meaningful enterprise GenAI cloud experience.
- Proven experience deploying and supporting AI/ML systems in production.
- Strong understanding of LLM application architecture and enterprise AI implementation.
- Excellent client-facing and consulting communication skills.
- Ability to explain architecture decisions, technical trade-offs, and AI/ML solutions to non-technical stakeholders.
- Willingness and ability to attend an in-person interview in Santa Clara, CA.
Nice-to-Have Skills
- Experience in the Energy / Utilities / Oil & Gas / Natural Resources domain.
- Experience with Databricks and/or Snowflake.
- Experience with ML frameworks such as XGBoost or CatBoost.
- Experience with LLMOps, AI evaluation frameworks, and GenAI observability/evaluation tooling.
- Experience working with enterprise products and customer-facing consulting engagements.
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