Principal Data Scientist

Bunge has an exciting opportunity available for a Principal Data Scientist. This role will be part of a global team working on challenging, meaningful projects impacting core business activities. Since 1818 Bunge has been connecting farmers to consumers to deliver essential food, feed and fuel to the world. Looking to the future, our ambition is to continuously reinvent ourselves leveraging data to be at the forefront of analytics technology and talent to accomplish our purpose in a better, faster and simpler way. Bunge is committed to operating and thriving in the digital world, creating world‑class agile teams where teammates are empowered and encouraged to collaborate, test and learn to succeed. At Bunge people don’t just come here to work; they come here to grow by solving challenges that directly impact the world with a diverse team of thinkers and doers. Bunge offers a strong compensation and benefits package, generous paid time‑off program, flexible work arrangements and opportunity to progress. Our hybrid work environment provides a balance of in‑office and remote work. Most importantly, in all we do we live our values: Act as One Team by fostering inclusion, collaboration and respect. Drive for Excellence by being agile, innovative and efficient. Do What’s Right by acting safely, ethically and sustainably. Overview: We are seeking a highly motivated and experienced Principal Data Scientist with strong expertise in pricing optimisation to join our growing team. As Principal Data Scientist you will be a critical technical lead of the Business Technology, Data and Analytics team, responsible for leading the construction and optimisation of large‑scale models to solve business problems and communicate the value to the business stakeholders. You will also be responsible for working with cross‑functional teams to identify and prioritise data analytics initiatives driving significant impact throughout our global value chains. Essential Functions : Main Accountabilities Design, create, test and implement complex modelling and algorithmic systems that drive value throughout the organisation. Lead large‑scale data science initiatives from POC to production. Design and structure a reusable codebase utilising data‑science best practices and support the sustainability of our technical portfolio. Collaborate with various stakeholders to understand business problems and implement scalable and sustainable solutions. Work closely with Data Scientists, Analysts and Data Engineers to build and deliver valuable analytical solutions. Communicate and document the design, functioning and output of the analytical models/solutions developed to a variety of audiences. Ensure timely deliverables and testing for regular maintenance of solutions over time. Communicate data insights and value articulation to stakeholders. Serve as a technical lead and point of contact to product managers, business partners and collaborators. Contribute to a culture of learning through technical mentoring and tool sharing. Major Opportunities and Decisions The problems faced are difficult and often complex and multi‑dimensional. Decisions and problem‑solving are guided by policies, procedures and the business plan; anticipate and interpret internal or external issues and recommend solutions and best practices. Apply acquired expertise to analyse and solve problems without clear precedent. Management/Leadership Manage operational plans for large projects and/or processes with limited oversight from a manager. Lead and/or participate with comparable influence in large projects/initiatives and/or provide leadership to professionals and support. Contribute to short‑to‑mid‑term (1–3 years) talent optimisation plans to execute on strategies in the job area. Key Relationships, Stakeholders & Interfaces Stakeholders include leadership team members, business leaders and technical experts. Strong interpersonal and soft skills are important. Be tech‑savvy and business‑savvy and understand different types of data‑analytics technologies, applying methods to valuable authentication and fraud prevention. Shape data products in alignment with corporate strategy and provide data insights leading to business directions. Postgraduate degree in STEM field or bachelor’s degree with a combination of 5 years of experience in Data Science or Computer Science, IT or a related field. Strong foundations in maths, analytics and computer science; knowledge of machine‑learning methods, statistical models and advanced data‑science programming. 5 years of hands‑on experience and fluency in Python and SQL; comfortable with scripting language such as Bash. Experience writing reusable and maintainable code with version control and the ability to transform a project from POC to production. Experience building and deploying resilient data and modelling pipelines in the cloud environment. Experience with at least one major cloud platform (GCP, AWS or Azure) with preference to GCP services such as Compute Engine, BigQuery, Cloud Run and Cloud Composer. Creative and self‑motivated; demonstrate drive to learn new skills and solve challenging problems. Act as a great team player in a global environment; take responsibility to consistently build better solutions both in technical quality and business impact. Preferred Qualifications Good understanding of software‑development best practice and ability to apply that to machine‑learning projects including unit tests and CI/CD integration. Experience using Infrastructure as Code (IaC) such as Terraform. Experience implementing Kubernetes and Docker (or similar container engine) solutions. Obtained Google Cloud Professional certifications in areas such as MLE, Data Engineer or DevOps Engineer. Experience working with customer analytics and pricing optimisation and domain knowledge in global agri‑business is a plus. Required Experience: Staff IC Key Skills: Machine Learning, Python, Data Science, AI, R, Research Experience, Sensors, Drug Discovery, Research & Development, Natural Language Processing, Data Analysis Skills, Toxicology Experience Employment Type: Full Time Location: Sao Paulo, São Paulo (BR-SP), Brazil (BR) #J-18808-Ljbffr