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5 дней назад

Senior Data Scientist (Machine Learning)

200 000 - 250 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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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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