Sr Data Scientist II

DoubleVerify

Paris

Sur place

EUR 56 000 - 101 000

Plein temps

14 jours+

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Résumé du poste

DoubleVerify, located in Paris, is seeking a Senior Data Scientist II to design and optimize world-class bidding algorithms that enhance ad performance. This role involves analytical rigour and a strong command of statistical methods applied to large datasets.

The ideal candidate will have a master's degree in applied mathematics and over three years of programming experience, preferably in languages like Python or C++. Familiarity with DevOps practices and cloud environments is essential.

The estimated salary range for this position is between €56,000 - €101,000, along with potential bonuses and benefits.

Qualifications

  • 3+ years of programming experience in Python, C++, C#, or similar languages.
  • Experience with DevOps tools like Git, CI/CD, Docker.
  • Strong communication skills and ability to work in agile teams.

Responsabilités

  • Evaluate and improve optimization algorithms.
  • Design and develop new products and features.
  • Work with massive datasets and investigate issues.

Connaissances

Programming in Python
Statistical methods
DevOps (Git, CI/CD)
Machine Learning
Cloud environment familiarity

Formation

Masters degree in applied mathematics

Outils

Docker
Kubernetes

Description du poste

DoubleVerify provides an End-to-end, comprehensive measurement and granular optimization. DoubleVerify is the recognized market innovator with the technology and tools that accurately authenticate the quality of digital media and drive ad performance for the world's largest brands. DV provides media transparency and accountability to deliver the highest level of impression quality for maximum advertising performance. Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best‑in‑class solutions across the digital ecosystem that help build a better industry. Learn more at doubleverify.com

The Role:

As a Senior Data Scientist II, you own new initiatives, design, build and scale world-class bidding algorithms to optimize ad performance. This position will combine analytical rigour, a relentless curiosity, a strong knowledge of statistical methods and experience in implementing them.

What you will do:
  • Evaluate and improve DV Scibids optimization algorithms.
  • Design, develop and test DV Scibids new products and features.
  • Work with massive datasets (billions of ad impressions/month) and millions of variables.
  • Operate production environments, investigate issues, assess their impact, and develop feasible solutions.
  • Work in multi-functional agile teams with end-to-end responsibility for product development and delivery.
  • Continuously release features using automated deployment tools and framework through Infra-As-Code.
  • Provide code reviews and system design for team members.
Who you are:
  • Masters degree in applied mathematics (e.g. machine learning, statistics, probabilities, operations research).
  • 3+ years of programming experience, preferably in Python, C++, C# or a similar language.
  • Experience with DevOps domain - Git, CI/CD, Docker, and container clusters (Kubernetes).
  • Familiarity with the Cloud environment.
  • Strong communication skills and a team player.
  • You provide mentoring to mid-level engineers.
  • Passion for automation and data-driven decisions.
  • Care about agile software processes, data-driven development, reliability, and responsible experimentation.
  • Familiarity with the AdTech specific technical challenges is not required, but is a plus.

The successful candidate’s base salary will be determined based on a number of non-discriminatory factors, including qualifications for the role, level, skills, experience, location, and internal equity considerations.

The estimated salary range for this role based on the qualifications set forth in the job description is between €56,000 - €101,000. This role may also be eligible for bonus or commission (as applicable), equity and benefits.

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