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Data Scientist (m/f/d)

Kayzenβ€’Austria, Germany, Switzerlandβ€’πŸŒ Remote
Full-timeMid Level
πŸ‘οΈ 0 viewsβ€’πŸ“ 0 applicationsβ€’Posted 10/15/2026β€’Expires 11/14/2026
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Job Description

Data Scientist (m/f/d) Europe, Remote HelloπŸ‘‹I am Puneet , Co-founder and CPO at Kayzen , and I am now looking for a Data Scientist to join our team πŸ™Œ But wait, you have not heard of Kayzen before? πŸ˜ƒ Kayzen is a mobile demand-side platform (DSP) dedicated to democratizing programmatic advertising.

We enable leading apps, agencies, media buyers, and brands to run programmatic customer acquisition, retargeting, and brand performance campaigns through its self-serve and managed service options.

Built on the three core pillars of performance, transparency, and control, Kayzen powers the world’s best mobile marketing teams with bespoke solutions that fuel business growth and deliver a competitive advantage. With an unprecedented scale of 160B+ daily ad requests from 1.

6B+ unique users worldwide, we serve up to 1B+ ads per day in 180 countries. Kayzen is accessible through our APIs and user interface.

The Team You will work with a carefully selected, diverse and globally distributed Data Science team (like Heiko, Chen) on various machine-learning models that process terabytes of data, serving billions of ad requests and users around the globe in real-time.

We are highly motivated and aligned in our quest to disrupt the multi-billion dollar ad-tech industry. We would like you to be part of our journey, as our Data Scientist (m/f/d) .

Responsibilities

Our day-to-day work in Data Science and Machine Learning encompasses a wide range of activities, including: Enhancing Models: Continuously improving existing models by incorporating new features, fine-tuning parameters, and utilizing additional data.

Algorithm Development: Collaborating with our Machine Learning Engineering team to develop and deploy scalable supervised and unsupervised learning algorithms. Data Exploration: Identifying and exploring new data sources while researching innovative ways to leverage both new and existing data effectively.

Solution Research: Investigating new Machine Learning solutions to optimize

Required Skills

Data ScienceMachine Learning

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