Meshy is a Silicon Valley–based company and a global leader in 3D generative AI. We are redefining the 3D content creation workflow through cutting-edge AI technology. Our platform enables both professional creators and hobbyists to effortlessly generate high-quality 3D assets — transforming text or images into detailed 3D models within minutes.
What previously required weeks of work and cost up to $1,000 can now be completed in just 2 minutes for $1. Meshy is fundamentally improving the efficiency and accessibility of 3D creation.
Our team includes top talent from MIT, Stanford, UC Berkeley, Nvidia, Microsoft, and other leading institutions and technology companies. With team members across North America, Asia, and Oceania, we foster a highly diverse and globally collaborative innovation culture.
Meshy is backed by top-tier venture capital firms including Sequoia and GGV, with $100 million raised across Series A and B. According to the A16Z Games 2024 report, Meshy is the most popular 3D AI tool. Based on SimilarWeb data, the platform receives over 4 million monthly visits. We have more than 7 million registered users and have generated over 70 million 3D models to date.
Founder and CEO Yuanming (Ethan) Hu holds a PhD from MIT in computer graphics and AI. He is the creator of the open-source GPU programming language Taichi (27K+ GitHub stars, adopted by 300+ research institutions). His research has been nominated for the SIGGRAPH Best PhD Thesis Award and has received 2,700+ academic citations.
We are hiring a Data Analyst Intern to own two integrated pillars of our analytics work:
Dashboard migration — moving existing visualizations from Databricks, Metabase, and Tableau onto Hex, our new AI-powered analytics platform.
Analysis and proactive insights — running ad-hoc analyses, investigating anomalies you uncover along the way, and producing business insights that leads to key business decisions.
The pillars feed each other: as you migrate dashboards, you will notice anomalies worth investigating; as you investigate, you will sharpen the metric definitions and chart selections that go into the new dashboards.
This is a real, cross-functional project touching every business team at Meshy. You will get end-to-end ownership across the full scope above: scoping requirements with stakeholders, rebuilding dashboards in Hex with AI assistance, validating data parity, investigating what the data is telling you, and handing off polished work to stakeholders. The technical bar is intentionally accessible (the underlying data is already there), but the role demands attention to detail, patience, strong communication, and a genuine appetite for learning new AI tools.
This is not a ticket-execution role. We expect you to think critically throughout: which charts are obsolete? Which metrics could be defined better? Why is this segment behaving differently? What does Faye or the Growth team need to know that they haven't asked yet?
Audit existing dashboards on Databricks, Metabase, and Tableau and define migration priority.
Rebuild visualizations on Hex with exact data parity to the original.
Design and run validation procedures (row counts, aggregate checks, sampled dimension comparisons).
Improve on the new dashboards with new metrics and visualizations.
Maintain a clear migration tracker (status, owner, blockers).
Before migrating each dashboard, proactively engage stakeholders:
Which charts and metrics are still actively used? Which can be deprecated?
What additional dimensions or metrics would they want in the new version?
Identify opportunities to enrich data and sharpen metric definitions so business teams can pinpoint issues more accurately. Push for standardized, documented metric definitions.
Leverage Hex's built-in AI to auto-draft chart skeletons and speed up migration.
Use Python (pandas, plotly) for complex visualizations that AI cannot generate out-of-the-box.
Explore modern interactive patterns on Hex (parameterized notebooks, AI-assisted exploration). Aim to make the new dashboards better than the old ones, not just equivalent.
Validate every AI-generated output. Build the habit of "AI accelerates, human verifies."
Investigate anomalies that surface during migration — unexpected trends, KPI drift, segments behaving differently than expected. Treat dashboards as starting points, not endpoints.
Translate stakeholder questions ("why did weekend conversion dip?", "which segment has the highest 30-day retention?") into structured analyses with clear conclusions and recommended next steps.
Produce concise written insights and readouts for non-technical audiences — Slack updates, doc summaries, short Hex narrative notebooks.
Support deep-dive investigations across growth, retention, conversion, and monetization in collaboration with senior analysts.
Bring a hypothesis-driven mindset: form a hypothesis, test it with data, revise based on findings — don't just describe what the numbers show.
Work with Product, Growth, Marketing, Finance, and other business teams to understand actual usage patterns.
Run short walkthroughs and handoffs after migration to ensure smooth adoption.
Present analytical findings in a way non-technical stakeholders can act on. A good insight changes a decision; a forgettable one just gets nodded at.
Communicate effectively in async environments (Slack, Feishu).
Currently pursuing a Bachelor’s, Master’s, or PhD degree (Math, Stats, CS, Economics, Information Systems, or related fields preferred).
Solid SQL (JOINs, GROUP BY, window functions, CTEs).
Hands-on experience with at least one data visualization tool (Tableau, Looker, Hex, Metabase, Power BI, or Python visualization libraries).
Fluent in both Chinese and English (written and verbal).
Detail-oriented, patient, and accountable. Migration work demands "every number must be right."
Curiosity-driven analytical mindset. Can form a hypothesis, test it with data, and revise based on findings. Doesn't just describe what the numbers show — asks why.
Comfortable communicating a business insight to a non-technical audience in 2 to 3 sentences, with a clear "so what."
Basic statistical literacy. Understands mean vs median, sample size intuition, awareness of confounding variables, and the difference between correlation and causation.
Practical experience using AI tools (ChatGPT, Claude, Cursor) with awareness that AI outputs must be verified.
Prior Hex experience.
Basic understanding of SaaS, subscription, or growth metrics.
Python data analysis or visualization (pandas, plotly, matplotlib).
Has previously owned a dashboard or data product end-to-end.
Familiarity with product analytics tools (PostHog, Amplitude, Mixpanel).
Exposure to A/B testing, experiment readouts, or causal inference basics.
Meticulous. Silent data mismatches are the biggest enemy of a migration project.
Proactive. Surface improvements the stakeholder didn't ask for.
Uses AI but doesn't trust it blindly. Accelerator, not authority.
Fast learner. Can pick up Hex and Python libraries from docs without hand-holding.
Clear communicator. Talks to non-data teams in business language, not jargon.
Competitive compensation and equity, allowing you to share in the company's growth
Opportunity to build AI-first data systems at the forefront of the AIGC industry
Flat, open, and engineering-driven culture that encourages innovation and self-motivation
Direct impact on product and business decisions
Collaboration with top-tier AI researchers and product teams, with strong personal growth opportunities
Comprehensive benefits package (social insurance, housing fund, annual health checkups, paid annual leave, team-building activities, etc.)
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