Data-Driven Growth Specialist, Faraday Future

• Experience: 3-5 years of professional experience in performance marketing, growth, SEO/GEO, data-driven marketing, or related roles, ideally combining both B2C consumer-technology and B2B segments. Track record of owning a measurable growth or conversion number
• Education: Bachelor's degree in Marketing, Business, Computer Science, Statistics, Economics, or a related field. Advanced degree a plus but not required
• Paid Digital Marketing Expertise: Proven CPL and CAC results running paid digital marketing campaigns on TikTok, Meta, YouTube, LinkedIn, and programmatic platforms. Hands-on experience with bidding optimization, audience targeting, creative testing, and media budget management. Able to independently read attribution reports, diagnose funnel issues, and ship corrective tests without analyst support
• GEO & Search Strategy: Hands-on experience with llms.txt, Schema.org structured data, JSON-LD knowledge graphs, technical SEO fundamentals, and the post-Google LLM answer ecosystem (Claude, ChatGPT, Gemini, Perplexity)
• AI & Automation Fluency: You build with Claude, GPT, and similar models. You write prompts as production code, ship versioned prompt libraries, and have personally delivered at least one non-trivial AI agent or automation workflow that runs in production
• Tool Fluency: Working command of n8n / Make / Zapier, GA4, Google Tag Manager, HubSpot or Salesforce, a data warehouse (BigQuery, Snowflake, or equivalent), and a BI tool (Looker, Metabase, or Hex)
• Technical Skills: SQL is required. Working-level Python or JavaScript for scripting and lightweight integrations. Comfortable reading API documentation and shipping a working third-party integration end-to-end
• Experimentation Discipline: Demonstrated ability to design, run, and document a high volume of growth experiments with clear hypotheses, success criteria, and shareable learnings
• Bilingual: Strong proficiency in both English and Mandarin Chinese, both verbal and written, with the ability to translate complex product and technical messaging into clear, conversion-friendly content for CN and US audiences
• Cross-Functional Agility: Comfortable operating across paid media, organic, content, brand, sales, and engineering functions in a fast-moving, matrix-style organization with multiple concurrent priorities

Desirable

• The Data-Driven Growth Specialist will join Faraday Future's Content Commerce Center, owning the full data-to-revenue path across GEO search authority, paid digital marketing and performance media, full-funnel conversion, and AI-powered growth automation.
• This role is responsible for turning every traffic source — paid digital, organic, social, and LLM-driven — into measurable qualified leads and revenue
• This is a builder role, not a manager role. The Specialist operates as a high-leverage growth function — designing systems, shipping automations, and compounding AI-augmented workflows rather than coordinating headcount
• The bar is leverage, not scale of team. Every manual task done twice becomes an automation; every automation compounds into FF's growth operating system
• GEO Search Authority: Own Faraday Future's answer share inside Claude, ChatGPT, Gemini, Perplexity, and emerging LLM-powered search surfaces. Deploy and maintain llms.txt, 100+ FAQ structured data, JSON-LD schema graphs, and a canonical content library that LLMs preferentially cite. Monitor citation share weekly and ship content fixes within 72 hours of any loss in priority prompts
• Paid Digital Marketing & Performance Media: Plan, execute, and optimize full-funnel paid digital marketing across TikTok, Meta, YouTube, LinkedIn, programmatic display, and emerging AI-native ad surfaces. Operate TikTok ACA with daily creative rotation, drive LinkedIn ABM (Thought Leader Ads, Document Ads) for B2B targets, and own landing-page CRO across the ROI calculator, deposit cart, and lead-capture flows. Manage media budgets, bidding strategies, and audience targeting end-to-end. Performance is measured in CPL and CAC, not impressions
• Full-Funnel User Growth: Grow qualified leads from low baseline to 1,000+ per month through programmatic experimentation, cohort and LTV analysis, and matrix-scale distribution. Run a minimum of 20 documented growth experiments per quarter with public win-loss logs so every learning compounds into the team's playbook
• AI Workflow & Agent Engineering: Build and maintain the systems that allow one operator to do the work of ten. Develop and version a Claude / GPT / Gemini prompt library covering market research, copywriting, creative ideation, competitor monitoring, and dashboard generation. Architect n8n / Make pipelines connecting ad platforms, CRM, analytics, and Slack. Use Claude Code and MCP servers to automate reporting, anomaly detection, and brand-safety content audits
• Data Infrastructure & Attribution: Build and own the closed-loop attribution model connecting GA4, TikTok Pixel, Meta CAPI, LinkedIn Conversions API, and the company CRM. Maintain live dashboards that surface ROI down to the single ad-creative level. Replace weekly slide decks with always-on data products
• Lead Engine Operations: Operate the OpenClaw + ManyChat + AI scoring stack with the AI Workflow Center to achieve sub-10-minute lead capture, sub-5-minute scoring, and sub-30-minute dealer dispatch. Continuously calibrate lead scoring models, dealer dispatch rules, and AI SDR handoffs in partnership with the Sales Conversion team
• Cross-Functional Collaboration: Partner with the Global Social Media Center (GSMC) on social-sourced leads and Owner-aligned content for paid amplification; with the Visual Creative Center (VCC) on conversion creative briefs and asset-library feedback loops; with the Matrix & KOC team on systematic scale-out of winning creative across the matrix network; and with the AI Workflow Center on co-owned engineering of growth automation
• Compounding Leverage & Knowledge Sharing: Document prompts, agents, dashboards, and playbooks in a continuously versioned Growth OS. Train other team members on AI-augmented workflows. Treat every manual repetition as a defect — automate or systematize on the second occurrence