Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Мало
$93к-160к/год
$150к$180кмедиана$210к
По похожим ролям (49) ~ $180к/год
На СНГ рынке: $4.4к/мес ($3.8к - $6к)
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Хорошая вакансия
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Чёткие задачи по моделированию мошенничества, актуальный стек и крупная компания делают вакансию привлекательной, но работа описана скорее как роль с поддержкой команды, чем как позиция senior-уровня.
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Ниже рынкаУровень под вопросомАктуальный стекАктуальная специализация
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Data Scientist (Fraud Risk Detection): Building and evaluating machine learning models and features that identify fraud across account opening, account takeover, and identity risk with an accent on feature engineering, model evaluation, and production deployment. Focus on investigating attack patterns, optimizing precision, recall, fraud capture, and customer friction, and implementing explainable and governed solutions.
Location: Remote within the United States
Salary: $92,562–$160,440 annually, plus variable pay opportunity
Company
hirify.global is a global data and technology company serving financial services, healthcare, automotive, insurance, agribusiness, and other markets across 32 countries.
What you will do
Explore complex datasets to identify fraud patterns, attack methods, and behavioral signals.
Translate fraud questions into testable hypotheses and investigate account opening, account takeover, and identity risk.
Build, train, validate, and evaluate machine learning models and features using technical and business metrics.
Develop features from identity, transactional, behavioral, and other data sources.
Write clean, well-tested code and collaborate with engineering to deploy models and features to production.
Support model and feature monitoring, client-focused research, analysis, and communication with technical and nontechnical audiences while following privacy, documentation, explainability, validation, and governance standards.
Requirements
3+ years of experience in data science, machine learning, statistical modeling, or a related quantitative field.
Bachelor's or advanced degree in computer science, statistics, mathematics, economics, engineering, data science, or another quantitative discipline.
Foundation in supervised learning, model evaluation, feature selection, statistical inference, classification, and anomaly detection.
Proficiency in Python, including clean, readable, and well-tested code.
Familiarity with pandas, NumPy, and scikit-learn.
Investigative mindset and ability to turn unusual data patterns into testable hypotheses.
Familiarity with PySpark, cloud platforms such as Amazon Web Services, Google Cloud, Azure, Databricks, Snowflake, or other large-scale data tools.
Exposure to financial services, FinTech, payments, or another regulated or fraud-intensive industry through coursework, internship, or prior work.
Culture & Benefits
Remote role with a flexible work environment; remote, hybrid, and in-office arrangements are supported.
Medical, dental, vision, and matching 401(k) benefits.
Flexible time off, including volunteer time off, vacation, sick leave, and 12 paid holidays.
Compensation package and bonus plan.
Inclusive, purpose-driven, people-first culture.
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