Senior Data Scientist (GenAI & Utilities)

Dear Job Seeker,

We have an opening with one of our client Senior Data Scientist (GenAI & Utilities) position. This is a long-term contract; Location Corpus Christi, TX - Hybrid

This is a fast-moving opportunity, and the client is looking to fill the position as soon as possible with a highly skilled candidate who is the right match for the role.

If you feel your skills and experience match this position, please don’t hesitate to apply or reach out to me. We’d be happy to discuss the opportunity with you.

Position: Senior Data Scientist (GenAI & Utilities)

Location: Corpus Christi, TX - Hybrid

Duration: Long-term

Job Overview:

1. Hierarch Soft Technologies is seeking an experienced Senior Data Scientist (GenAI & Utilities) for a long-term contract opportunity with one of our clients in Corpus Christi, TX. This position will focus on building a specialized AI task force to leverage generative AI for operational excellence, including infrastructure maintenance, grid optimization, and enhanced customer support.

2. The ideal candidate will have strong hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, database integration, and modernization initiatives. The individual should understand the technical challenges involved in translating unstructured operational data into actionable insights and be capable of helping design, implement, validate, and optimize intelligent AI systems.

3. Given the scale and complexity of the utility network, the client is looking for a skilled professional who can contribute to model development activities, resolve technical challenges, improve RAG pipeline performance, and support ongoing advanced technology efforts.

4. This is a fast-moving opportunity, and the client is looking to fill the position as soon as possible.

Roles and Responsibilities:

5.         Database Migration: Support the integration and mapping of unstructured utility data, technical manuals, maintenance logs, and field reports into modern vector database systems.

6.         Database Architecture and Design: Review existing document structures and help design appropriate schemas, tables, relationships, embeddings, and vector database objects to support the target application environment.

7.         Legacy Database Analysis: Analyze existing utility data structures, asset management logs, SCADA alerts, and maintenance records to understand how legacy data should be represented in a relational and vector environment.

8.         Data Mapping and Conversion: Develop and review source-to-target data mappings, embedding rules, transformation logic, and ingestion procedures to ensure that unstructured data is correctly transferred into vector databases.

9.         SQL Development and Optimization: Write, review, and optimize SQL queries, prompt structures, and other database-related code as required to support data retrieval and application functionality.

10.       Database Performance Tuning: Identify and resolve performance bottlenecks by analyzing vector search latencies, indexing strategies, semantic search query performance, and LLM orchestration settings.

11.       Data Validation and Reconciliation: Perform data integrity checks, model evaluation testing, hallucination checks, and accuracy validation to ensure that generative AI outputs match source documentation and meet business requirements.

12.       Migration Planning and Execution: Assist with AI model deployment strategies, pipeline integration plans, testing procedures, production staging activities, and implementation schedules while minimizing disruption to existing business operations.

13.       Troubleshooting and Issue Resolution: Investigate and resolve technical issues related to RAG pipeline failures, data inconsistencies, prompt formatting, model latency, and system orchestration errors.

14.       Application and Database Integration: Work with software engineers, database administrators, data scientists, and other technical teams to identify dependencies between legacy systems and the target cloud environment (Azure/AWS).

15.       Database Modernization: Recommend improvements to vector database design, data access patterns, and model architectures to support long-term maintainability, scalability, and performance.

16.       Documentation: Prepare and maintain technical documentation covering existing data integration pipelines, RAG designs, prompt engineering guidelines, testing results, and model deployment procedures.

17.       Cross-Functional Collaboration: Collaborate with field operations, engineering teams, project managers, and other stakeholders to ensure AI activities align with project objectives, business data needs, and technical standards.

Required Technical Skills and Experience:

1. Strong hands-on experience with Python, PyTorch or TensorFlow, and relational database architecture using SQL.

2. Experience supporting advanced framework integration using LangChain or LlamaIndex for enterprise application transformation projects.

3. Understanding of vector embedding concepts and the challenges involved in converting legacy unstructured files into high-quality semantic search vectors.

4. Experience with database schema design, data modeling, prompt engineering, semantic indexing, and search optimization.

5. Ability to analyze complex unstructured data formats and translate them into appropriate relational or vector database designs.

6. Experience with data mapping, vectorization, output validation, reconciliation, and model evaluation testing.

7. Strong troubleshooting, analytical, and problem-solving skills.

8. Ability to work collaboratively with cross-functional technical and operational teams.

9. Excellent communication skills and the ability to explain complex technical AI concepts clearly.

Preferred Qualifications:

1. Direct experience with vector database environments such as Pinecone, Milvus, or Weaviate.

2. Previous experience designing and fine-tuning Large Language Models (such as GPT-4 or Llama 3) for enterprise solutions.

3. Experience with system modernization and enterprise machine learning pipeline conversion projects.

4. Familiarity with asset management systems, infrastructure data, SCADA logs, and industrial application dependencies, where applicable.

5. Experience planning AI model deployment testing, production cloud cutovers, and post-deployment validation in AWS or Azure.

6. Knowledge of LLM performance tuning, token optimization, and context window management techniques.

Ideal Candidate Profile:

• The ideal candidate is a technically strong Data Science professional with 10+ years of experience who understands both machine learning architecture and the practical challenges of deploying GenAI and RAG pipelines. Candidates with direct experience in the utility, energy, oil & gas, or heavy industrial sectors will be particularly relevant.
• The client is looking for someone who can assess existing unstructured data environments, contribute to generative AI strategy and execution, troubleshoot complex technical model issues, and help ensure that the target RAG environment is reliable, efficient, and maintainable.

How to Apply:

• If your skills and experience align with this opportunity, or if you know someone who may be a suitable fit, please apply or reach out to Hierarch Soft Technologies to discuss the position further.
• This is a long-term contract opportunity with a hybrid work arrangement in Corpus Christi, TX. The client is looking to move quickly with the right candidate.