• Resilience over accuracy. Don’t build models that only work well for a short time; instead, build models that stand the test of time.
• Own your models. Take responsibility for accidental mistakes and be aware that your actions will impact your organization.
• Deploy early, monitor, and iterate. Only deployments show true success. Monitor and use challengers for additional optimizations.
• Impact over optimization. Focus on business impact, not data science challenges. Always keep the ROI in mind.
• Upright and ethical. Data science should be about finding the truth. Your job is not to look good; your job is to have real impact.
• Simplicity first, no waste. The simplest possible model is often the best model. It is easier to understand anyway. Be thoughtful about resources.

source:https://rapidminer.com/blog/data-science-manifesto/