Data Scientist

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)., 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 every step of our value chain.
• A/B Testing: Regularly conducting and evaluating A/B tests to drive insights and refine our strategies.

You’ll be a great fit if you resonate with the following principles of Data Science and Machine Learning:

• Simplicity First: We prioritize finding the best solutions to challenges rather than forcing problems to fit predetermined solutions.
• Impact-Driven: We leverage Machine Learning to enhance our product and drive performance for our clients, always focusing on tangible business outcomes.
• Collaborative Spirit: Our teams consist of analysts, engineers, and data scientists, making strong communication skills essential for success.
• Embrace Experimentation: We believe in the power of experimentation to innovate and refine our approach continually., * Directly working with Founders and an opportunity to drive direct impact
• Exceptional career growth and learning opportunity
• A unique opportunity to be part of an experienced team of industry experts and entrepreneurs who bring massive change to the Adtech market
• A fun, driven, and multinational team located across Germany, India, Argentina, Canada, Spain, the UK and many more countries.
• A flexible work-from-home arrangement
• Opportunity to relocate to our office in Berlin
• A 500-dollar home-office setup budget
• A 1000-dollar annual learning and development budget

• At least 3 years of relevant experience in developing data science products, from initial research through to production deployment.
• Strong coding skills with a focus on clean, reproducible, and well-tested code.
• Proficient in key tools and technologies including Python, Spark, Hadoop, Airflow, Docker, and SQL.
• Hands-on experience with algorithms for handling sparse and large datasets, including applications in prediction, clustering, and outlier detection.
• Familiarity with Gradient Boosting Trees (CatBoost, LightGBM) in production environments is a plus.
• Experience in building neural network-based products for tasks such as classification, regression, and multi-task learning is highly valuable.
• Bonus skills: Knowledge of reinforcement learning and large-scale optimization problems is a significant asset.
• Good understanding of dashboards and SQL for developing and enhancing monitoring tools.
• Previous experience in Ad-Tech is a must.

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.