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Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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$200к-250к/год
$160к$200кмедиана$220к
По похожим ролям (48) ~ $200к/год
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Крутая вакансия
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Чёткая зона ответственности за production-модели, понятные направления работы и подробное описание делают вакансию сильной; также предусмотрены наставничество и взаимодействие с бизнесом.
Полный цикл моделей
Актуальный стек
?Высокая планка
?Работа из офиса
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Data Scientist (Machine Learning): Building and deploying production machine learning models for experimentation, forecasting, pricing, and customer acquisition with an accent on model lifecycle ownership, large-scale data analysis, and business decision support. Focus on designing predictive models, developing forecasting and pricing expertise, and communicating complex results to technical and non-technical stakeholders.
Location: Hybrid, 3 days in office and 2 days remote, in New York, NY or Century City, CA
Salary: $200,000–$250,000 USD gross annual base pay.
Company
hirify.global operates a global marketplace for buying and selling tickets to live events, serving customers in 195 countries through hirify.global and viagogo.
What you will do
Build modeling solutions in experimentation, forecasting, pricing, or customer acquisition.
Design, develop, deploy, and own production machine learning models throughout their lifecycle.
Communicate modeling results and complex concepts to technical and non-technical audiences.
Act as a subject matter expert in predictive modeling, forecasting, and pricing.
Develop roadmaps with business partners and manage execution of independent projects.
Support junior team members and the broader data organization through workshops, best practices, and reading groups.
Requirements
7–11 years of relevant data science or machine learning experience.
Strong experience transforming and analyzing large-scale data using cloud computing platforms such as SparkSQL, BigQuery, Snowflake, or Databricks.
High proficiency with SQL.
Expertise in Python or R and numerical and scientific libraries for statistics and machine learning, such as Pandas, NumPy, SciPy, and scikit-learn.
Experience building production-level models in cloud environments such as AWS or Azure.
Ability to work with non-technical stakeholders to understand, anticipate, and deliver on data needs.
An MS or PhD in mathematics, statistics, computer science, or another quantitative field is preferred.
Nice to have
Proficiency in time series modeling, including GAMs, GLMs, or ARs, and real-time forecasting.
Culture & Benefits
Autonomy to lead experiments and tests at large scale in an accelerated growth environment.
Competitive compensation including base salary, equity, and upside tied to impact.
Unlimited flexible time off.
Benefits including 401(k), health, vision, dental insurance, paid parental leave, and comprehensive health coverage.
Culture focused on inclusion, results-oriented execution, open innovation, and creativity.
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