AI Data Scientist

We are looking for an AI Data Scientist to own the behavioral intelligence layer of a new platform that converts raw, multi-modal user data into structured, high-value behavioral signals.
Users opt in and are compensated with crypto tokens in exchange for sharing data from their devices and digital activity. The output is premium behavioral data: intent signals, decision‑making context, preference hierarchies, and real behavioral patterns, designed for AI companies, ad platforms, and market intelligence buyers who pay meaningful premiums for high‑quality data.
This role is not about dashboards or surface‑level analytics. You will define what data is worth collecting, how it should be extracted, and why it has commercial value, working backward from what downstream buyers actually want.
You will work closely with the founding team on data strategy, privacy boundaries, and product direction.
Responsibilities    Signal Triage & Prioritization  Develop a strong understanding of what AI companies, data buyers, and intelligence platforms pay for. Understand why certain behavioral signals are worth significantly more than generic clickstreams and how intent + context create premium datasets.

Screen & Session Intelligence  Define the boundary between raw data (which may contain PII or sensitive UI) and clean, anonymized extracted intelligence. Specify what is processed locally vs. in the cloud and establish PII detection and filtering rules before data leaves the device.

Noise Reduction at Scale  Build relevance scoring and filtering frameworks to avoid collecting, storing, and processing low‑value or redundant data. Help define what types of user data‑sharing sessions produce the highest‑value intelligence for downstream buyers. Ensure behavioral data extracted from different environments can be unified into a coherent, standardized data product.

Success Factors  We are looking for a thoughtful, opinionated data scientist who can operate in ambiguity and make hard calls about what not to build.
Ability to think from the buyer’s perspective, not just the collector’s
Comfort challenging assumptions with evidence
Bias toward clean, defensible data products over “collect everything” approaches
Qualifications   3–7+ years of experience in data science, applied ML, or quantitative research
Experience working with messy, real‑world, multi‑source data

Experience with computer vision, OCR, or video/image processing pipelines
Proficiency in Python and the modern ML/data stack (PyTorch, Tensor Flow, OpenCV, OCR tooling, pandas, Spark, or equivalent)
Working knowledge of privacy concepts (PII, anonymization, local vs. cloud processing)
Comfort operating in early‑stage, low‑structure environments
Nice to Have   Experience working with or alongside AI companies focused on training data or model evaluation
Background in data monetization, data marketplaces, or data licensing

Experience with on‑device or edge ML
Familiarity with token‑based incentive systems or crypto payouts
Experience in ad tech, market research, or behavioral analytics

How to Apply

We are looking for intellectually curious builders who are excited by hard, ambiguous problems.
You can apply via the platform where you found this job posting (e.g., Linked In).
We will acknowledge receipt of applications within 48 hours and notify candidates selected for the next step within 7 days. Please check your inbox and spam folders to avoid missing communications.
GoQuant Technologies Inc. is an Equal Opportunity Employer.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.

#J-18808-Ljbffr