Senior Data Scientist, Business Analytics

Job not on LinkedIn

🔥 3 minutes ago

🦬 Wyoming – Remote

🦬 Wyoming – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Venice.ai

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2024

🤖 Artificial Intelligence

☁️ SaaS

🔌 API

🔥 Funding within the last year

💰 $65M Series A on 2026-06

Artificial Intelligence • SaaS • API

Venice. ai is a privacy-focused AI platform that provides access to leading third-party and open-source models for generating text, images, video, audio, code, embeddings, and agents. The company emphasizes user privacy through anonymized access, zero data retention for self-hosted models, Trusted Execution Environments (TEEs), and client-side end-to-end encryption. Venice offers a unified API compatible with OpenAI and agent stacks, developer tools (SDKs, LangChain, OpenAI SDK compatibility), and products for creators and enterprises with tiered pricing plans. Its features include multimodal generation, image and video creation/editing/upscaling, text-to-speech and music generation, and support for uncensored models.

📋 Description

• Own data end to end, including data sourcing, storage, flow, access, querying, infrastructure, tooling, dashboards, and insights • Consolidate access to financial statements, product metrics, and growth analysis • Build a shared data lake with specialized views • Support experiment tracking by building systems for Product to monitor tests • Proactively identify and answer strategic business and product questions • Derive insights using available data and statistical methods suitable for small samples • Communicate uncertainty and provide recommendations with appropriate caveats • Assess the existing data warehouse and product analytics tooling, identify gaps, and build what is missing • Build dashboards, self-serve analysis tools, data models, and reporting pipelines • Partner with product, engineering, finance, marketing, and executive stakeholders • Work with engineering to instrument products thoughtfully while minimizing unnecessary data collection • Support finance metrics, marketing growth attribution, and executive company-level metrics • Protect user privacy and advise on data-collection tradeoffs • Build robust metrics that distinguish signal from noise in a rapidly changing product

🎯 Requirements

• 7+ years of demonstrated experience • Product-minded data leadership with engineering depth • Ability to translate business questions into analysis and recommendations • Experience working with messy, incomplete, or deliberately constrained data • Experience with quasi-experiments, proxy metrics, qualitative triangulation, and decision frameworks • Production-quality coding skills • Fluency in SQL • Ability to build data pipelines, data models, and tooling • Understanding of data warehousing concepts and modern analytics stacks • Experience with PostHog for product analytics • Experience with Postgres for data storage and querying • Understanding of PostHog as a platform across error tracking, support, and conversation data • Familiarity with Rust, TypeScript, Go, and Python; familiarity with more than one is a plus • Ability to communicate clearly with executive stakeholders, including uncertainty and confidence levels • Respect for Venice’s privacy mission and agreement with its data-minimization principles • Ability to move quickly, iterate, and use AI agents/LLMs to accelerate analysis and automate repetitive data work

🏖️ Benefits

• Opportunity to help shape a fast-growing consumer AI company • Opportunity to work with AI agents, LLMs, and modern analytics tooling • Privacy-first work environment centered on user sovereignty and data minimization

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