Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global visual discovery and inspiration platform connects millions of people around the world with creative ideas and possibilities. The organization is focused on helping people discover inspiration, plan for the future, and create meaningful experiences while using technology, data, and artificial intelligence to enhance its platform and impact.
The organization is seeking a Sr. Data Scientist, Performance Marketing to bring greater scientific rigor to marketing measurement and optimization. This role will influence strategic decisions related to user growth, marketing investment, user behavior, engagement, and lifetime value.
Key Responsibilities
- Conduct deep strategic analysis to answer growth marketing questions, including how to increase monthly active users through paid performance marketing.
- Quantify the impact of paid performance marketing in new markets and identify opportunities to improve user engagement and lifetime value.
- Evolve existing geo-testing and incrementality testing frameworks.
- Build and deploy statistical and machine learning models, including propensity, forecasting, and lifetime value models.
- Develop, maintain, and improve models related to user lifetime value, marketing budgets, and long-term user retention.
- Collaborate with cross-functional teams to address a wide range of product and business challenges.
- Advance experimentation capabilities and tools for evaluating the business impact of performance marketing investments.
- Advise teams on experimentation best practices, identify weaknesses in experimental approaches, and develop tools for experiment analysis.
- Define appropriate success metrics for teams and manage their complete lifecycle, including logging requirements, metric definitions, prototype pipelines, and ongoing improvements.
- Translate complex analytical findings into clear, actionable insights and strategic recommendations for technical and non-technical stakeholders, including senior leadership.
- Develop clear analyses that help teams identify opportunities and improve existing strategies.
- Design, maintain, and promote dashboards and automated reporting tools that enable self-service, data-driven decision-making.
- Build and optimize ETL data pipelines to automate reporting, support deep-dive analysis, and facilitate feature engineering for analytical models.
- Lead key technical projects and contribute to strategic marketing analytics initiatives.
Required Qualifications
- 5+ years of combined postgraduate academic and industry experience applying scientific methods to real-world problems.
- Master’s degree in a quantitative field such as mathematics, statistics, computer science, engineering, or a related discipline.
- Hands-on experience developing marketing measurement solutions to quantify the business impact of marketing tactics and investments.
- Strong foundation in statistics and quantitative analysis, with experience applying advanced statistical techniques to practical business problems.
- Expertise in at least one scripting language, preferably Python or R.
- Strong proficiency in SQL/Hive and the ability to write efficient SQL queries.
- Strong business and product judgment.
- Ability to transform ambiguous business questions into well-defined analyses and measurable success criteria.
- Excellent communication skills, with the ability to lead initiatives and present findings to senior leadership and cross-functional teams.
- Ability to clearly and concisely explain analytical approaches, methodologies, and thought processes.
- Experience leading significant technical projects.
- Strong experimentation background and statistical rigor.
- Experience working on causal inference projects.
Preferred Skills and Experience
- Experience with performance marketing analytics and optimization.
- Experience developing marketing attribution and measurement frameworks.
- Strong understanding of experimentation methodologies and incrementality testing.
- Experience building statistical and machine learning models for marketing optimization.
- Experience working with user growth, retention, engagement, and lifetime value metrics.
- Experience developing automated reporting systems, dashboards, and analytical data pipelines.
- Ability to work effectively with multidisciplinary teams across Marketing, Product, Engineering, Analytics, and Data Engineering.
Disclaimer
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