Gen AI Data Scientist

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IN THIS ROLE

In this role, you will have the opportunity to contribute to developing a cutting-edge Commercial Reporting solution with AI and GenAI capabilities. You will play an instrumental part in building AI and GenAI solutions, harnessing large data sets from across the organization, and collaborating with cross-functional teams and stakeholders to meet business requirements.

WHAT THIS TEAM AND ROLE DOES

Our team is at the forefront of driving AI, data, and analytics in US Sales & Planning. As a Data Scientist within the Mondelez Digital Solutions team, you will work towards the following objectives:

• Utilize Analytical AI algorithms (e.g., linear regression, decision trees, boosted trees models) to automatically gather insights that will be presented in the commercial reporting solution of the company.

• Leverage anomaly detection algorithms (e.g., isolation forest) to identify anomalies within the data and generate alerts for the commercial reporting team.

• Leverage Large Language Models (LLMs) to build GenAI capabilities to help the commercial reporting team summarize the current state of the business and explain the why behind the numbers.

WHAT YOU WILL BRING

• Proficiency in designing and deploying Analytical AI solutions that drive actionable insights.

• Familiarity with the concepts and applications of GenAI in various domains, especially text generation.

• Dedication to translating complex data scenarios into tangible business strategies.

• Outstanding communication skills, excelling in breaking down intricate AI/ML concepts for a diverse audience.

JOB REQUIREMENTS

• Design, develop, and implement AI models to gather insights about customers, brands, categories and products for the commercial reporting team.

• Leverage GenAI models for generating innovative insightsand improve the way reporting is done at Mondelez.

• Work collaboratively with multiple teams to ensure smooth implementation of the Analytical AI and GenAI capabilities into the company dashboard.

• Regularly update and refine the AI and GenAI solution with new data sources and features.

• Oversee the extraction, preparation, and utilization of large datasets required for model training, validation, and implementation, ensuring data quality and relevance.

• Maintain comprehensive documentation of AI models and GenAI solutions, their logic, and performance metrics.

• Regularly report on the tool's achievements, challenges, and suggested enhancements to senior management and relevant stakeholders.

SPECIFIC SKILLS AND EXPERIENCES

• Bachelor's degree in Information Systems/Technology, Computer Science, Analytics, or a related field.

• Strong analytical and critical thinking skills, with the ability to identify challenges and propose practical solutions.

• Proficient in handling large datasets using Python and SQL.

• Proficiency in data visualization tools (e.g., Tableau, PowerBI).

• Familiarity with cloud platforms (e.g., Google Cloud, Azure, Databricks) for deploying AI solutions.

• Experience with data preprocessing, cleaning, and ETL processes.

• Experience with Natural Language Processing (NLP) techniques.

• Knowledge of recent advancements and trends in GenAI, demonstrating a commitment to continuous learning in this rapidly evolving field.

• Basic understanding of the ethical implications of GenAI, including issues related to bias, fairness, and the use of synthetic data.

• Understanding of the consumer goods industry or Retail or similar industries.

GOOD TO HAVE SKILLS AND EXPERIENCES

• Working knowledge of syndicated data (e.g., Nielsen/IRI or other EPOS/Retail Sales data source.)

• Proficiency in using data containerization and orchestration tools to create and maintain complex data workflows.

• Experience with additional programming languages, such as PySpark and R.

• Experience with leveraging Large Language Models (LLMs) to build GenAI proof-of-concepts and/or solutions.

• Experience with Langchain or similar frameworks for building language applications.

• Minimum 6+ years of relevant experience required.