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Senior Data Scientist | BEES Personalization
Отличная вакансия в глобальной компании с сильной инженерной культурой и современным стеком (Azure, Databricks). Предлагается широкий соцпакет и возможность работать над продуктами, влияющими на реальный бизнес в мировом масштабе.
Сложность вакансии
Высокая сложность обусловлена требованием Senior-уровня, глубоких знаний PySpark и опыта работы с облачными платформами (Azure/Databricks) для обработки больших данных. Также ожидается опыт менторства и владение современными алгоритмами глубокого обучения.
Анализ зарплаты
Зарплата для Senior Data Scientist в Бразилии (где базируются офисы BEES) обычно варьируется от 15,000 до 25,000 BRL в месяц. Учитывая глобальный статус AB InBev, предложение, скорее всего, находится на верхнем уровне рынка или включает значительные бонусы.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Data Scientist position within the BEES Personalization team at AB InBev. With a solid background in developing and deploying advanced machine learning models, particularly in the areas of recommendation systems and portfolio optimization, I am confident in my ability to contribute to your mission of putting customers at the heart of digital transformation.
Throughout my career, I have gained extensive experience working with large-scale data processing using PySpark and Databricks within Azure environments. I have a proven track record of translating complex business requirements into scalable technical solutions, and I am particularly drawn to this role's focus on frontier algorithms and the opportunity to mentor junior scientists. My expertise in building end-to-end ML pipelines and my commitment to technical excellence align perfectly with the goals of the BEES Applied Science team.
I am excited about the prospect of bringing my skills in deep learning and automation to AB InBev and helping drive innovation across your B2B e-commerce platform. Thank you for considering my application.
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Описание вакансии
About BEES
BEES, our ambition is – and always will be – to put customers at the heart of everything we do. Making their lives easier and their businesses more profitable. Through our B2B e-commerce and SaaS platform, we bring the power of digital to small and medium-sized retailers and the companies that service them, unlocking new growth opportunities for all. With offices in São Paulo and Campinas, we encourage our team to participate in major events and significant meetings throughout the year.
The Team: BEES is the team driving AI strategy at BEES by building end-to-end products to serve our teams, customers, and partners across the globe. The organization is a cross-functional blend of AI/ML teams from Applied Research and Machine Learning Engineering to Machine Learning Platform Product Management. Together, the team is responsible for building the tools and products needed to deliver world-class AI/ML capabilities
As a member of BEES Applied Science team, you will develop solutions for challenging business problems in areas such as portfolio optimization, recommendations, personalization, promos, segmentation, imputation, and insights discovery. The ideal candidate should hold a bachelor's degree in any quantitative field; strong mastery of frontier algorithms in machine and deep learning; plus working knowledge of cloud platforms (Azure, Databricks) for ML applications. Proficiency in python / pyspark programming, collaboration tools, and working knowledge of CI/CD tools like GitHub is required. Knowledge of workflows for automation is also required.
What you will do:
- Collaborate on the design of complex analysis of datasets and the development and deployment of advanced machine learning and deep learning algorithms for portfolio optimization, recommendations, personalization, promos, segmentation, imputation, and insight discovery. Ensure that solutions are robust, scalable, and aligned with business objectives while mentoring junior and mid-level data scientists.
- Actively stimulate the machine learning and deep learning update on advancements, continuously incorporating cutting-edge techniques to solve complex business problems. Champion the adoption of frontier algorithms to drive innovation and technical excellence across the team’s initiatives.
- Architect and optimize large-scale data processing workflows on cloud platforms such as Azure, Databricks, and Spark, ensuring performance and scalability. Guide best practices in leveraging these platforms to accelerate delivery.
- Support the design and implementation of reliable data pipelines and modeling workflows using Python and PySpark. Introduce automation and reusable components that enhance team productivity and reduce operational overhead.
- Engage proactively with cross-functional teams—including data engineering, product management, and business stakeholders—to translate business needs into technical requirements and deliver impactful, end-to-end solutions. Foster an agile mindset, driving rapid iteration and continuous improvement.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or any quantitative field; Master’s or PhD strongly preferred.
- Demonstrated success applying machine learning and statistical modeling techniques in production environments to drive measurable business impact.
- Experience mentoring and coaching data scientists and engineers, fostering skill development and knowledge sharing within cross-functional teams.
- Experience working with cloud platforms such as Azure, Databricks, and Spark for big data processing and analysis.
- Exceptional communication skills, with the ability to translate complex technical concepts into clear, actionable insights for both technical and non-technical stakeholders.
- 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\*
- Private pension plan
- Meal Allowance
- Casual office and dress code
- Days off\*
- Health, dental, and life insurance
- Medicines discounts
- WellHub partnership
- Childcare subsidies
- Discounts on Ambev products\*
- Clube Ben partnership
- Scholarship\*
- School materials assurance
- Language and training platforms
- Transport allowance
\*Rules applied
Equal Opportunity & Affirmative Action:
AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. 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.
The following fields are optional, but anticipate the information for your registration\*.
Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company.
For more information: www.abinbev.com
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Навыки
- Python
- PySpark
- Azure
- Databricks
- Machine Learning
- Deep Learning
- GitHub
- CI/CD
- Apache Spark
- Statistical Modeling
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Расскажите о вашем опыте оптимизации производительности PySpark заданий при работе с терабайтными датасетами. С какими узкими местами вы сталкивались?
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