Data Scientist Technician

Posting number: J101321-260716

Department: Information Technology

Job classification: Data Scientist Technician

Posting type: Open & Promotional

Categories: IT and Computers

Summary

Under general supervision from the IT Assistant Director (EA, Dev & Cyber), is responsible for designing, building and optimizing an on-premises AI knowledge platform.  This job class is treated as FLSA Non-Exempt.

Essential Functions: Essential functions may vary among positions and may include the following tasks, knowledge, abilities, skills and other characteristics.  This list of tasks is ILLUSTRATIVE ONLY and is not intended to be a comprehensive listing of tasks performed by all positions in this classification.

Examples of duties

1. Designs and implements Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge systems.  Supports all aspects of in-life products, including customer feedback, requirements, and issues.

2. Integrates local LLMs with vector databases to support question answering, summarization and semantic search.

3. Builds and optimizes embedding pipelines for both structured and unstructured datasets. Evaluates retrieval performance and using ranking metrics and retrieval benchmarks.

4. Collects and analyzes feedback from customers, stakeholders and other teams to shape requirements, features and products. Analyzes usage data and continuously refines retrieval pipelines.

5. Translates business knowledge into searchable and retrievable AI knowledge systems.\

6. Creates test plans and assists in the execution of user acceptance test cases.  Leads end-user testing sessions and training.

7. Provides timely and accurate updates of individual progress, communicating all variations to commitments as they are known.

8. Performs other job-related tasks as assigned by the Assistant IT Director (EA, Dev & Cyber) or IT Director/CIO.

Knowledge, Skills, Abilities and Other Characteristics:

• Knowledge of enterprise knowledge management and search platforms.
• Knowledge of software development and implementation methodologies, with an emphasis on Retrieval-Augmented Generation (RAG) approaches.
• Knowledge of SQL and database querying.
• Knowledge of vector databases, information retrieval concepts (BM25, ranking, scoring), embedding models and semantic search.
• Knowledge of both manual and automated testing.
• Knowledge of conducting User Acceptance Testing.
• Knowledge of Agile Software Development Lifecycle Methodologies with an emphasis on Kanban, Sprints and iterations.

 

• Skill with verbal and written communication.
• Skill eliciting requirements from customers and end-users.
• Excellent organizational and time management skills.
• Sharp analytical and problem-solving skills.
• Skill teaching software system usage in one-on-one and classroom settings.

• Ability to effectively handle change management and requirements gathering.
• Ability to develop and maintain positive and effective working relationships with all levels of the department and Community.
• Ability to work independently and manage multiple concurrent tasks effectively.
• Ability to learn quickly and be willing to tackle tasks requiring advanced problem-solving skills.
• Ability to interact with computer users at all levels of staff and at all levels of computer experience.

Qualifications

Education: A bachelor’s degree from an accredited college or university in Information Systems, Management Information Systems, Computer Science, Engineering or a closely related discipline.

Experience:

• 1 year demonstrated experience with data science, machine learning and Natural Language Processing (NLP) required.
• 1 year demonstrated product development experience of on-premises RAG architectures and LLM integration required.
• 1 year demonstrated successful experience in the following required:

• • Proficiency in various programming languages with a data science focus, primarily Python and Java paired with data science libraries.
  • Experience with document parsing and large document sets.
  • Experience with vector databases and embedding workflows.
  • Advanced SQL and data analysis.
  • Working directly with engineering teams to design and iterate on products.
  • Manual and automated testing.

• Demonstrated successful experience in the following preferred