Data Scientist
3 meses atrás
Kaizen Gaming is the leading GameTech company in Greece and one of the fastest-growing in the world, operating in 16 markets with 2 brands, Betano & Stoiximan. We always aim to leverage cutting-edge technology, providing the best experience to our millions of customers who trust us for their entertainment. We are a diverse team of more than 2,500 Kaizeners, from 40+ nationalities spreading across 3 continents. Our #oneteam is proud to be among the Best Workplaces in Europe and certified Great Place to Work across our offices. Here, there'll be no average day for you. Ready to press play on potential? Role Overview At Kaizen, our aim is to make data-driven decisions in order to automate our services while also focusing on offering tailored customer experiences. Our machine learning team is dedicated to this mission by building a variety of models, from binary classification tasks to recommendation systems. We focus on transforming business needs into production applications and cover a wide range of business sectors utilizing different data types and handling broad project diversity. Our teams comprise three different roles: data scientists, machine learning engineers, and data engineers, ensuring we have the full skill set to deliver projects to production. Responsibilities As a Data Scientist, you will: Translate business requirements to machine learning problems; Perform EDA and featureengineering; Implement best practices on model selection, parameter tuning, etc. What You'll Bring A background in Computer Science, Statistics, Math, or a related field; Strong knowledge of machine learning algorithms and respective theory; 2-8 years of hands-on experience in delivering machine learning models to production; Knowledge of the Pythonmachine learning ecosystem; Experience with Spark (PySpark); Solid software background in OOP; Strong skills in teamwork, communication, and analytical thinking; Fluency in English, both oral and written. Nice to Have Experience with Azure / Databricks; Knowledge of Deep Learning; Experience in recommendation systems. Benefits Hybrid way of working & remote options; A buddy will support you with your onboarding; Competitive pay and bonus scheme; Unlimited access to Udemy & continuous training; Private health insurance for you & your family; Monthly meal allowance; Commuting allowance; Nice Rigs - 2.5K monitor, latest i7, tons of RAM, fast SSD. Recruitment Privacy Notice: Regarding the data you share with us, you may find and read our recruitment privacy notice here. #J-18808-Ljbffr
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