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Marketing Data Scientist (AI/ML)

104 000 - 156 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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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

hirify.global 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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