Data Scientist
bet365 is seeking a Data Scientist to join the Data Analytics team. You will develop machine learning solutions and perform statistical analyses to inform strategic, data-driven decisions across our Sports and Gaming products. You will extract insights from large datasets, develop predictive models, and contribute to data-led decision making across various business functions. Collaborate with stakeholders from Fraud, Responsible Gambling, Trading, and Branding to identify opportunities, solve complex problems, and build robust data solutions using a modern tech stack in a fast-paced, high-volume environment. This role is eligible for our hybrid work-from-home policy.
Data Scientist
bet365 is seeking a Data Scientist to join the Data Analytics team. You will develop machine learning solutions and perform statistical analyses to inform strategic, data-driven decisions across our Sports and Gaming products. You will extract insights from large datasets, develop predictive models, and contribute to data-led decision making across various business functions. Collaborate with stakeholders from Fraud, Responsible Gambling, Trading, and Branding to identify opportunities, solve complex problems, and build robust data solutions using a modern tech stack in a fast-paced, high-volume environment. This role is eligible for our hybrid work-from-home policy.
Qualifications: - PhD in Computer Science, Statistics, Mathematics, or related quantitative field. - Experience with core ML techniques: regressions, classification, clustering, deep learning. - Strong programming skills in Python, R, SQL. - Familiarity with data science libraries, data mining, data warehousing, and data visualization. - Knowledge of AI and its application in data science. - Strong communication skills with technical and non-technical audiences. - Knowledge of cloud computing, distributed systems, and big data technologies.
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Qualifications: - PhD in Computer Science, Statistics, Mathematics, or related quantitative field. - Experience with core ML techniques: regressions, classification, clustering, deep learning. - Strong programming skills in Python, R, SQL. - Familiarity with data science libraries, data mining, data warehousing, and data visualization. - Knowledge of AI and its application in data science. - Strong communication skills with technical and non-technical audiences. - Knowledge of cloud computing, distributed systems, and big data technologies.
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Based on: Data Scientist
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