However, the article also highlights a knowledge gap in the field, with 81% of survey respondents holding an advanced degree in a related field. To bridge this gap, the article suggests businesses train their data scientists in optimization, particularly those with a strong mathematics background. This would enable them to make better business decisions and meet future business challenges.
Key takeaways:
- Mathematical optimization is slowly joining the data science mainstream, with more than 80% of surveyed companies combining it with machine learning.
- The number of practitioners with one to three years of optimization experience grew by 25% in 2023, indicating a growing interest and need for talent in this field.
- Mathematical optimization is expanding beyond traditional domains like logistics and supply chain management, with increasing use in areas like finance, telecommunications, healthcare, energy and environmental management.
- There is a significant knowledge gap in the field of mathematical optimization, with 81% of survey respondents holding an advanced degree in a related field. Bridging this gap with more accessible tools and resources is crucial for the field's growth.