Data Science Engineer

Дата размещения вакансии: 30.03.2020
Работодатель: Wrike
Уровень зарплаты:
з/п не указана
Город:
Санкт-Петербург
Требуемый опыт работы:
От 3 до 6 лет

We owe our success to our talented and energetic team of smart, friendly, and professional employees, and we're looking for the same qualities in you! At Wrike, we believe that work should be both challenging and fun. We're growing rapidly and providing excellent opportunities for professional development.

We're growing our ML expertise and creating ML features for Wrike users so they can improve their productivity. We're looking for a Senior Data Scientist, who will become a key person on our product ML team and DS/ML department. You'll work with the product and engineering organization, participate in the initial research of potential features, set up numerous hypotheses validations and drive them to product realization with ML team, tune tooling, and help other ML engineers to grow.

Responsibilities:

  • Communicate with other DS/ML engineers, product owners, and developers
  • Create, formalize, and validate hypotheses
  • Train models for both hypotheses evaluation and production
  • Present results to the product organization
  • Help deliver product features
  • Contribute to ML infrastructure (internal frameworks, logging and data organisation, etc.)
  • Mentor people and drive the technical growth of the DS/ML team

Requirements:

  • Strong mathematical background (ability to read and understand recent research papers)
  • 3+ years of experience working with statistical modeling, machine learning, or related fields
  • Ability to write clean and efficient code (Python is preferable)

Would be a plus:

  • Participating in hackathons and Kaggle competitions
  • Experience in NLP or graph analysis/SNA
  • Experience working with Google Cloud Platform

Our advantages:

  • High involvement in selecting research directions
  • Large amount of structured and unstructured user activity data
  • Mature company data culture (separate team of data engineers, product analysts, and ML Engineers)