BEES

Runs a digital ordering platform for small retailers

Intermediate Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeCampinas - State of São Paulo, BrazilIn-person

About the Job

Requirements

A bachelor's degree in computer science, engineering, mathematics, or a quantitative field is required.
Strong technical skills and a deep understanding of frontier machine learning and deep learning algorithms are required, including familiarity with portfolio optimization, recommendations, personalization, promotions, segmentation, imputation, and insights discovery techniques.
Proficiency with machine learning frameworks such as TensorFlow or PyTorch and experience implementing and deploying models using them are required.
Experience with cloud platforms such as Azure, Databricks, and Spark for big data processing and analysis is required.
Proficiency in Python and PySpark for data manipulation, analysis, and modeling, with strong knowledge of relevant libraries and frameworks, is required.
Good knowledge of CI/CD tools such as GitHub for version control and collaboration is required.
Understanding of workflows and automation tools to streamline processes and improve efficiency is required.

Responsibilities

Collaborate with team members to analyze complex datasets and develop and implement machine learning and deep learning algorithms for portfolio optimization, recommendations, personalization, promotions, segmentation, imputation, and insights discovery.
Stay current with machine learning and deep learning advancements and apply frontier algorithms to solve business problems and drive innovation across team projects.
Use Azure, Databricks, and Spark to process and analyze large-scale datasets and deliver scalable, performant solutions.
Use Python and PySpark for data manipulation, analysis, and modeling, and implement automation workflows to streamline processes and improve productivity.
Collaborate with data engineers, business stakeholders, and product managers to understand project requirements and deliver solutions using an agile development approach.

Desired Qualifications

A master's degree is a plus.
Familiarity with additional collaboration tools is a plus.

About BEES

Join us to build the future of B2B commerce!
BEES is AB InBev’s B2B platform. Through our ecosystem, merchants and retailers across 29 countries can stock their businesses quickly, easily, and securely.
At BEES, we dream big, lead with purpose, and develop technology that transforms the way retailers and sellers grow. Every line of code and every partnership is built in service of a single mission: to make commerce better for retailers and sellers around the world. Here, your work is not just important. It makes a difference!

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*
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

About the Company

BEES

Runs a digital ordering platform for small retailers

BEES runs a business-to-business commerce platform where small and medium-sized retailers order stock from brewer AB InBev and other consumer brands. AB InBev created it to digitize how its brands reach retailers, and other brand owners and distributors use the same system to run their own sales and delivery. Its connected tools cover ordering, payments, delivery management, customer service and data for management teams. Built-in AI recommends products and offers to each retailer and plans sales visits and delivery routes for field teams. BEES first ran in the Dominican Republic before expanding to other countries, and it is headquartered in Rotkreuz, Switzerland.

Company size: 501-1,000
Company stage: Not listed
Total funding: Not listed
Headquarters: Risch-Rotkreuz, Switzerland
Founded: 2019

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