Embedding VC - Data Scientist
Requirements
• Bachelor's or above in a quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field • Minimum 3 years of work experience in analytics or data science • 3 years • Expert SQL • Python • Deep understanding of statistical analysis, experimentation design, and common analytical techniques such as regression and decision trees • Strong product intuition — able to connect numbers to user behavior and product decisions • Strong verbal and written communication skills; able to tell clear data stories to both technical and non-technical audiences • A humble, collaborative, can-do attitude and natural curiosity • High ownership, fast execution, and strong attention to detail • Experience as the first or early DS hire at a startup • Experience working with consumer products, marketplaces, or creator/UGC platforms • Familiarity with experimentation platforms and causal inference methods • Experience with BigQuery, Amplitude, Metabase, or similar tools in data stack • Experience partnering with marketing/growth teams (LTV, retention, funnel analysis) • Exposure to AI/ML products or generative AI • Comfort working across time zones with a globally distributed team • BigQuery, SQL, Python, Amplitude, Metabase, Stripe, GCP
Responsibilities
• Product leadership: use data to shape product development, quantify new opportunities, set goals, identify upcoming challenges, and ensure the products we build bring value to our customers. • Product leadership • Analytics: develop hypotheses and employ a diverse toolkit of rigorous analytical approaches — different methodologies, frameworks, and technical techniques — to test them. • Experimentation: design, run, and analyze A/B tests and other causal experiments; help establish the experimentation culture and standards across the company. • Experimentation • Metrics and measurement: define and own key product metrics, build dashboards, and ensure leaders and teams have accurate, trusted data to make decisions. • Metrics and measurement • User and behavioral analysis: deep-dive into how users create, share, and engage on OpenArt to surface insights that drive retention, engagement, and monetization. • User and behavioral analysis • Communication and influence: convince and influence your partners by telling clear data stories — translate complex analyses into crisp recommendations for PMs, engineers, and execs. • Communication and influence • Cross-functional partnership: collaborate with Data Engineering on instrumentation and pipelines, with Product/Eng on feature design and measurement, and with Marketing/Finance on growth and revenue analytics. • Cross-functional partnership • Build the function: establish DS best practices, mentor over time, and help shape the team as it grows. • Build the function
Benefits
• First Data Scientist hire in the US — set the bar, shape the function, and build the foundation of OpenArt's data science practice. • First Data Scientist hire in the US • Direct impact on product strategy — your work shapes what we build, how we prioritize, and how we measure success. • Work across product, engineering, data, marketing, and finance — one of the most cross-functional roles in the company. • Build from 0 → 1 — define how we use data to drive product decisions at OpenArt. • High ownership, low process, fast iteration environment. • 7–10X revenue growth over the past 2 years — now scaling our data and analytics infrastructure to match. • Competitive base salary and bonus program • Equity — meaningful ownership in what you build • High autonomy, high growth environment • 🌍 Work Setup • 🌍 Work Setup • Bay Area preferred (hybrid allowed) • Visa sponsorship available • We’ll consider remote
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