GOALS

• Leverage AI and ML to personalize customer experiences, optimize pricing strategies, and improve customer segmentation for targeted marketing campaigns
• Develop predictive models to forecast demand, optimize inventory management, and minimize supply chain disruptions
• Build a data-driven culture within the organization by empowering teams with self-service analytics tools and insights

Frustrations

• Dealing with large volumes of unstructured data from various sources, making it challenging to clean, process, and prepare for AI model training
• The rapidly evolving nature of AI and ML technologies requires continuous learning and upskilling to stay current with the latest advancements
• Ensuring the accuracy, reliability, and interpretability of AI models to build trust and confidence in data-driven decisions

GOALS

• Develop innovative AI and ML algorithms to improve product recommendations, personalize user experiences, and enhance fraud detection systems
• Experiment with and implement cutting-edge deep learning techniques to solve complex business problems and gain insights from unstructured data
• Contribute to the development of scalable and efficient AI pipelines for data processing, model training, and deployment

Frustrations

• Limited access to labeled training data for specific AI tasks, requiring time-consuming data labeling efforts
• Difficulty explaining complex AI model outputs to non-technical stakeholders in a clear and understandable way
• Keeping up with the rapid pace of research and development in the AI field and identifying the most relevant advancements for practical applications