обновлено 5 дней назад
Marketing Data Scientist (AI/ML)
104 000 - 156 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Marketing Data Scientist (AI/ML): Analyzing marketing performance and developing scalable AI/ML solutions for payments and digital cash products with an accent on campaign measurement, customer lifecycle analytics, and marketing optimization. Focus on designing experiments, building predictive models and LLM-enabled solutions, integrating machine learning into business workflows, and communicating actionable insights to cross-functional stakeholders.
Location: Hybrid schedule with onsite presence in Cupertino, California, United States; not open to relocation candidates.
Salary: $104,000–$156,000 per year, depending on experience.
Company
develops analytical solutions for payments and digital cash products within a global payments ecosystem.
What you will do
- Analyze marketing and business performance with SQL, Python, and statistical methods to identify actionable insights.
- Design A/B tests, multivariate experiments, and causal inference analyses to evaluate campaign effectiveness.
- Develop and deploy AI/ML models for segmentation, churn prediction, recommendations, targeting, personalization, and marketing optimization.
- Integrate machine learning outputs into business workflows for automation and real-time marketing optimization.
- Advise marketing leaders on campaign design, measurement frameworks, and data-driven storytelling.
- Present insights using Keynote, Tableau, and other visualization tools while collaborating with engineering, product, and finance.
Requirements
- 3+ years of experience in data science, marketing analytics, or a related quantitative field, preferably in an enterprise context.
- Experience working with large, complex datasets and translating raw data into actionable business insights.
- Proficiency in SQL and Python, including pandas, scikit-learn, causalimpact, statsmodels, and LLM packages such as GPT and Claude.
- Strong knowledge of regression, classification, clustering, segmentation, predictive modeling, deep learning, and LLMs.
- Experience integrating machine learning outputs into marketing or business processes, plus expertise in experimental design, significance testing, and multivariate analysis.
- Advanced degree completed or in progress in data science, statistics, economics/econometrics, computer science, marketing science, operations research, mathematics, or engineering.
Culture & Benefits
- Fast-paced, curious, and collaborative working environment.
- Healthcare package with vision and dental coverage.
- Vacation and paid time off.
- Retirement plan.
- Support for continued learning and professional development.
- Hardware, software, and access to a Cupertino office.
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