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Intermediate Data Scientist – Bees Data Para Campinas

Tempo Integral
      Campinas       16/09

AB InBev | Growth Group

AB InBev | Growth Group está com vaga(s) de emprego para Intermediate Data Scientist – Bees Data Para Campinas em Campinas / SP

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Intermediate Data Scientist – Bees Data – campinas


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AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa. About AB InBev Growth Group Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world. In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft. We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities. What you will do: Collaborate with team members to analyze complex datasets, develop and implement cutting-edge machine learning and deep learning algorithms for portfolio optimization, recommendations, personalization, promos, segmentation, imputation, and insights discovery. Stay up to date with the latest advancements in machine learning and deep learning algorithms, ensuring a strong technical foundation to solve complex business problems. Apply frontier algorithms to drive innovation across the team's projects. Utilize cloud platforms like Azure, Databricks, and Spark to efficiently process and analyze large-scale datasets. Leverage the full potential of these platforms to deliver scalable and performant solutions. Utilize Python/PySpark for data manipulation, analysis, and modeling tasks. Implement automation workflows to streamline processes and enhance productivity using tools and frameworks. Collaborate closely with cross-functional teams, including data engineers, business stakeholders, and product managers, to understand project requirements and deliver high-quality solutions. Embrace an agile development approach to iterate quickly and efficiently. Qualifications: Bachelor's degree in computer science, engineering, mathematics, or any quantitative field. A master's degree is a plus. Strong technical skills and deep understanding of frontier algorithms in machine learning and deep learning. Familiarity with techniques for portfolio optimization, recommendations, personalization, promos, segmentation, imputation, and insights discovery. Proficiency in machine learning frameworks such as TensorFlow or PyTorch. Experience in implementing and deploying models using these frameworks. Experience working with cloud platforms such as Azure, Databricks, and Spark for big data processing and analysis. Proficiency in Python/PySpark for data manipulation, analysis, and modeling tasks. Strong knowledge of relevant libraries and frameworks. Good knowledge of CI/CD tools like Github for version control and collaboration. Familiarity with other collaboration tools is a plus. Understanding of workflows and automation tools to streamline processes and enhance efficiency. What We Offer: Performance based bonus* Attendance Bonus* Casual office and dress code Days off* Health, dental, and life insurance Discounts on Ambev products* School materials assurance Language and training platforms Equal Opportunity & Aff... AB InBev Growth Group is proud to be an Equal Opportunity and Aff... We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics. #J-18808-Ljbffr


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