Research & AI Data Operations Specialist

Position Title: Research & AI Data Operations Specialist

Organizations: Wizearly, Inc. & Oakland Natives Give Back (ONGB)
Location: Remote (U.S. or international with strong English proficiency)
Type: Part Time and Could Grow to Full-Time
Reports To: Founder & CEO, in collaboration with the Technical and Product Teams

About the Role

We are seeking a highly analytical, AI-savvy Research & Data Operations Specialist to join our growing innovation team at Wizearly, an AI-powered edtech startup predicting and preventing chronic absenteeism, and Oakland Natives Give Back (ONGB), a nonprofit improving educational outcomes for youth.

This is a hands-on role for someone who is equally comfortable designing datasets, conducting complex research, fine-tuning AI/LLM models, and building the structured data pipelines that power intelligent products.

You will work directly with leadership to research, curate, and label data; evaluate LLM outputs; document prompt engineering processes; and support the development of Wizearly’s AI-driven attendance and intervention models.

This position is ideal for an experienced LLM researcher, data analyst, or AI operations specialist who is eager to apply their skills to socially impactful education technology.

Key Responsibilities
AI Data Curation & Model Training

Research, collect, and clean large datasets to support machine-learning and LLM training.

Create structured prompts and response libraries for fine-tuning and evaluation.

Annotate, label, and QA training data with precision and context awareness.

Develop documentation, taxonomies, and metadata schemas for model interpretability.

Collaborate with data engineers or developers to build and maintain data pipelines.

Applied Research & Analysis

Conduct in-depth research on education, behavioral science, AI ethics, and data-driven intervention methodologies.

Synthesize findings into technical briefs, benchmark reports, and model documentation.

Use advanced statistical and data visualization tools (Python, R, SQL, Tableau, Power BI) to uncover actionable insights.

Evaluate model performance metrics and contribute to continuous improvement.

Process Design & Automation

Develop repeatable, automated workflows for data ingestion, tagging, and cleaning using AI tools (ChatGPT, Claude, LangChain, GPT-4 fine-tuning APIs, or similar).

Implement data quality assurance systems and version-control processes in Notion, Airtable, or Miro.

Recommend new tools, frameworks, and automation scripts to enhance data operations.

Cross-Functional Collaboration

Work closely with AI engineers, educators, and program teams to align data models with real-world educational applications.

Translate research findings into features, datasets, and AI behaviors that improve accuracy and fairness.

Provide expert feedback on prompt design, hallucination detection, and content moderation approaches.

Qualifications & Experience
Required

5+ years of experience in data analytics, AI research, or applied machine learning.

Proven experience training or fine-tuning LLMs (OpenAI, Anthropic, or similar).

Deep fluency in Python, Pandas, SQL, and modern data visualization tools.

Advanced proficiency with AI platforms and APIs (OpenAI, Hugging Face, LangChain, Weights & Biases, etc.).

Demonstrated ability to build and maintain clean datasets, perform quality control, and design annotation workflows.

Strong research methodology background — able to gather, evaluate, and synthesize complex information.

Excellent written communication and technical documentation skills.

Highly organized, self-directed, and able to operate at startup speed with minimal supervision.

Preferred

Experience in education, social impact, or behavioral data modeling.

Familiarity with edtech, student information systems (SIS), and FERPA-compliant data handling.

Prior work with classification models, embeddings, and supervised learning pipelines.

Experience building prompt evaluation frameworks or designing retrieval-augmented generation (RAG) systems.

Compensation

Competitive compensation commensurate with experience. Flexible structure (contract or FTE). Long-term growth opportunities exist within Wizearly’s R&D and AI development teams.