Scaled Business Growth
at Meta
Location
Menlo Park, CA; New York, NY; San Francisco, CA
Compensation
$161k–$227k USD
Type
full time
Posted
4 months ago
Market range · company + function + seniority
p25 · target · p75 · n=202
Posted $227k · in the market band
Posting health
Aging · 65- ·Open 144 days
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Job description
Meta empowers millions of businesses to connect with customers and drive real business outcomes. Scaled Business Marketing (SBM) is looking for a Scaled Business Growth Marketer to design data-driven programs that help businesses discover, adopt, and maximize the value of Meta's products. You'll work with cross-functional teams to unlock new opportunities, remove friction in the customer journey, scale high-impact solutions that drive measurable results, and help millions of businesses around the world succeed. This role requires someone who can analyze data & understand market trends to identify opportunities/challenges, design globally scalable marketing strategies and experiment/iterate while operationalizing what works to drive sustained business impact.
Responsibilities
- Lead marketing growth strategy across a large area and drive cross-team alignment.
- Identify and size marketing opportunities to drive material business impact.
- Design comprehensive, multi-channel marketing programs that accelerate outcomes across the funnel with a variety of audiences.
- Execute on projects by working closely with Product, Sales, Data Science, and other partners.
- Lead experimentation from designing tests to analyzing results that drive business impact.
- Leverage AI and advanced analytics to accelerate business impact.
Minimum Qualifications
- Bachelor's degree in a directly related field, or equivalent practical experience
- 8+ years of experience in growth marketing, digital marketing, marketing strategy, product growth, management consulting, or related field
- 7+ years of work experience in analytics - data extraction, querying, & interpretation with languages such as SQL including leveraging AI tooling
- 7+ years of experience developing and executing strategies to drive Marketing impact across multiple channels, combining quantitative analysis with qualitative customer insight to optimize performance and scale successful programs
- Experience developing & leveraging audience understanding via quantitative methods (segmentation, behavioral analysis) and qualitative methods (customer research, market insight), and translating findings into full-funnel marketing strategies
- Proficiency in quantitative analysis geared towards drawing actionable insights from complex datasets
- Experience designing & executing experiments, interpreting results, and translating findings into decisions
- Experience establishing KPIs, measurement frameworks, and attribution models, including incrementality and mixed media approaches, that connect marketing activities to business outcomes
- Proficiency in leveraging AI tools to accelerate business outcomes (e.g., audience research, personalization, content development, marketing optimization, etc.)
- Experience distilling complex data into compelling narratives and influence stakeholders at all levels of the organization
- Experience working with and influencing cross-functional teams including Product, Sales, Analytics, etc
- Experience working on marketing programs that reach a wide range of business customers Familiarity with advanced analytics including statistical analysis, predictive analytics, or machine learning applications in marketing
- Experience with data visualization tools (e.g., Tableau, Python, etc.) and ability to design executive-level dashboards that communicate complex insights to diverse audiences
- Knowledge of Meta's products and platform capabilities, or experience with similar technologies
- Demonstrated use of AI tools to accelerate core marketing capabilities
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
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