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1 месяц назад

Lead Data Scientist (AI/ML)

Формат работы
onsite
Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Lead Data Scientist (AI/ML): Driving analytics and modeling within the Finance organization to power growth and marketplace efficiency with an accent on framing ambiguous problems, developing robust models, and turning insights into actionable decisions. Focus on advancing core data science work, building scalable frameworks, and partnering with stakeholders to translate needs into solutions.

Location: Onsite in Toronto, Ontario, Canada

Company

hirify.global Inc. connects businesses with global, AI-enabled talent across various contingent work types through its Marketplace and Lifted solutions.

What you will do

  • Lead data science initiatives from exploration through delivery, defining metrics and success criteria.
  • Develop statistical and machine learning models to optimize marketplace systems such as search, pricing, and recommendations.
  • Build and maintain high-quality feature pipelines with clear data contracts and quality monitoring.
  • Set up and improve Data Science workflows for experiment tracking, reproducibility, and CI/CD practices.
  • Mentor peers through code reviews, model evaluations, and collaborative problem solving.
  • Translate complex analyses into insights that influence product, finance, and executive decisions.

Requirements

  • 5+ years of experience in Data Science, Applied Science, or a similar role delivering data-driven solutions at scale.
  • Advanced Python and SQL skills, including data manipulation with pandas, NumPy, and scikit-learn.
  • Familiarity with workflow tools such as Airflow, Dagster, or Spark.
  • Deep understanding of experimentation and statistical evaluation with a focus on business impact.
  • Hands-on experience with model development and evaluation, including feature engineering and error/bias analysis.
  • Practical MLOps expertise, including experiment tracking, containerization (e.g., Docker), version control, and leveraging feature stores.

Nice to have

  • Familiarity with dashboarding tools such as HEX and Tableau.
  • Comfort working with modern AI-assisted coding tools (e.g., ChatGPT, Cursor, Gemini).

Culture & Benefits

  • Access to company resources, culture, and growth opportunities.

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