Explore a conference talk that delves into the challenges of bridging the gap between research and software development in the context of a fertility app project. Learn about the discrepancies between code developed by scientists and software developers, and discover practical solutions using tools like MLflow for managing machine learning code lifecycles. Gain insights into real-world examples, potential solutions, and remaining challenges in integrating scientific research with software development practices. Understand how to improve collaboration between researchers and developers, and explore the application of frameworks like MLflow in data science projects.