AI Data Analyst

Velou; Palo Alto (CA); Hybrid; USD 27,552 - 41,328; Part time

Benefits offered by this job

Funded Prompt Engineering course certification

Collaborative environment with experienced analysts

Job summary

Velou, a Silicon Valley AI startup, seeks an AI Data Analyst to enhance product data enrichment. The role includes supporting AI workflows, evaluating model outputs, and utilizing LLM tools in a collaborative environment.

Ideal candidates are students in creative or commercial fields with strong cultural fluency, analytical skills, and a keen interest in consumer behavior. Training and a Prompt Engineering course certification are provided.

Qualifications

• Current students (second year and above) and recent graduates eligible.
• Strong analytical mind with an interest in structuring data.
• Hands-on experience with AI-assisted workflows or tools.

Responsibilities

• Support AI-driven enrichment workflows for product intelligence.
• Evaluate model outputs for accuracy and comprehensiveness.
• Document edge cases and contribute to clearer guidelines.

Skills

Cultural fluency

Fluency in English

Analytical thinking

Data quality assurance

Consumer culture awareness

Experience with AI tools

Education

Current student or recent graduate in a creative or commercial field

Tools

Data analysis tools

Spreadsheets

Job description

Velou is a Silicon Valley AI technology startup building the product‑data infrastructure behind the next generation of ecommerce. We turn raw catalogs into rich attributes and product copy and power smart discoverability, search, recommendations, and AI shopping agents customers buy through.

The Role

As an AI Data Analyst, you'll take ownership of a genuine slice of the enrichment engine that powers Velou's products. You'll work directly with our in‑house LLM models and shape the taxonomies and product intelligence.

Eligibility

• Eligibility: Current students (second year and above) and recent graduates.

What you’ll do

• Support our AI‑driven enrichment workflows and help build the taxonomy and product‑intelligence structures behind them—the categories, attributes, and relationships that make a catalog discoverable.
• Bring cultural and brand context to product data enrichment—reading the intent behind how customers shop, what a brand stands for, and who buys it, then translating that into how products are surfaced.
• Work hands‑on with our in‑house LLM models and AI tooling by helping fine‑tune them and shaping how they behave.
• Test and evaluate model outputs: assess enriched data for accuracy and comprehensiveness, and work with cross‑functional teams to improve quality.
• Turn client needs and business goals into concrete enrichment requirements.
• Document edge cases and contribute to clearer guidelines and standards.

What we’re looking for

• Strong cultural fluency is one of the most important skills we’re hiring for—built through any combination of study, work, media, or lived experience.
• Strong fluency in English, written and spoken. Clarity and precision in English are essential to the role.
• A student from a creative or commercial field. Fashion, design, marketing, media, or communications. Strong applicants from other backgrounds are welcome—we care more about how you think than what you studied.
• An analytical mind that prefers judgment over box‑ticking—you see patterns and reason clearly about how things should be structured, and can justify a call.
• Rigorous about data quality, structure, and reproducibility; you test your assumptions rather than trust them.
• Active interest in consumer culture and retail trends, in a cultural and global context, more specifically US consumer culture—have a working awareness of how consumer behavior differs across markets.
• Hands‑on experience with AI‑assisted workflows or tools, with some exposure to prompt engineering.
• Comfortable in a fast‑paced, evolving environment.
• Proficiency with data analysis tools and spreadsheets and basic LLM literacy is a plus.

What you’ll gain

• A funded Prompt Engineering course certification as part of your onboarding, alongside in‑house training on LLM workflows, fine‑tuning, and AI‑assisted tooling.
• A collaborative, forward‑thinking environment alongside experienced data analysts and engineers.