Data Scientist 1 Job in Mondelez
Job Summary
Company Overview Mondel z International is a leading global snacking company with iconic brands like Oreo, Cadbury, and Toblerone. The company s mission is to lead the future of snacking, creating delicious moments of joy for people around the world. As part of Mondel z's dynamic Digital Solutions team, this role will offer an exciting opportunity to drive innovation through AI, data, and analytics. Role Overview As a Data Scientist within the Mondelez Digital Solutions team, you will play a critical role in developing cutting-edge AI and GenAI solutions that will empower the US Sales & Planning teams. This role focuses on leveraging Analytical AI algorithms and Large Language Models (LLMs) to create actionable insights and transform commercial reporting processes. You'll work closely with multiple teams to implement these solutions and continuously improve the reporting and decision-making capabilities of the organization. How You Will Contribute 1. AI and GenAI Model Development Design, develop, and deploy Analytical AI models (e.g., linear regression, decision trees, boosted trees models) to gather insights related to customers, brands, categories, and products. Implement anomaly detection algorithms (e.g., isolation forest) to identify anomalies in commercial data and alert teams about significant changes. Utilize Large Language Models (LLMs) to summarize the current business state and explain trends in the data, supporting the commercial reporting team. 2. Data Preparation and Utilization Oversee the extraction, preparation, and utilization of large datasets for model training and validation, ensuring the data is clean, accurate, and relevant for AI model development. Continuously update and refine the AI/GenAI solution with new data sources and features to enhance business insights. 3. Collaboration and Implementation Work closely with cross-functional teams to ensure smooth deployment of AI and GenAI capabilities into the company s commercial reporting dashboards. Collaborate with stakeholders to ensure the tools meet business requirements and deliver high-quality insights. 4. Reporting and Documentation Regularly report on the achievements and challenges of the AI tools to senior management and relevant stakeholders. Maintain detailed documentation of AI models, GenAI solutions, logic, and performance metrics, ensuring the business can leverage insights effectively. 5. Continuous Improvement and Innovation Stay up to date with the latest trends in AI and GenAI and integrate new advancements into the reporting system to improve its efficiency and effectiveness. What You Will Bring 1. Required Skills & Experience Bachelor's degree in Information Systems/Technology, Computer Science, Analytics, or related fields. Strong analytical and critical thinking skills with the ability to translate complex data into actionable business strategies. Proficiency in handling large datasets using Python and SQL. Strong knowledge of data visualization tools such as Tableau and Power BI. Experience with cloud platforms (e.g., Google Cloud, Azure, Databricks) for deploying AI solutions. Experience with data preprocessing, cleaning, and ETL processes. Familiarity with Natural Language Processing (NLP) techniques. Knowledge of recent advancements and trends in GenAI and a passion for continuous learning in this field. 2. Additional Skills (Good to Have) Working knowledge of syndicated data (e.g., Nielsen/IRI or other retail sales data sources). Proficiency in using data containerization and orchestration tools for maintaining complex data workflows. Experience with programming languages like PySpark and R. Experience in leveraging Large Language Models (LLMs) to build GenAI solutions or proofs-of-concept. Experience with frameworks like Langchain for building language applications. Relocation and Support Within-country relocation support is available. For candidates voluntarily moving internationally, minimal support is offered through the Volunteer International Transfer Policy.
Qualification : Bachelor's degree in Information Systems/Technology, Computer Science, Analytics, or a related field.
Qualification : Bachelor's degree in Information Systems/Technology, Computer Science, Analytics, or a related field.
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