Here's how you can navigate the changing demands of clients and stakeholders as an Algorithm expert.

Understanding of current methods is essential. However, it is also essential to understand the limitations of the approaches being used. Don't follow what everyone else is doing blindly. Utilise knowledge gained on approaches to innovate and improve upon what is already available.

Staying abreast of the latest algorithmic and technological advancements is crucial. Engage actively by reading industry publications, attending conferences, and participating in online forums. These efforts provide valuable insights into emerging techniques and trends that may impact your work. Moreover, staying informed enables clear communication with clients and stakeholders, empowering you to provide informed guidance and make impactful decisions based on current technological landscapes.

Don't just learn new things it is good to be updated with the latest algorithms and technologies but also practice and have good hands-on on existing ones.

Always provide your opinion on each topic but first be a good listener and listen to what the other person is saying. Try to provide result driven solutions.

Anticipate challenges and propose proactive solutions. Educate stakeholders about algorithm complexities, document requirements and changes clearly, and use data to demonstrate effectiveness. This multifaceted approach ensures alignment with expectations, builds trust, and fosters successful project outcomes.

This is essential. Flexible thinking and problem solving helps meet the needs of the client whilst minimising the limitations of the approaches used. Sometimes the challenging needs of clients can help stimulate innovation and the broadening of capabilities.

Be willing to reconsider your approaches and be open to experimenting with different techniques. Sometimes, a problem may require an unconventional solution, and being flexible means you can think outside the traditional algorithmic box. This adaptability can lead to creative breakthroughs that satisfy stakeholder needs in ways they hadn't even considered.

Clear communication is essential. The groups we work with often come from diverse technological backgrounds. The audience may not understand high level approaches or results if they contain complex technical information. For example there are very few people working in the machine learning space who come from a biological background and cross disciplinary communication can be challenging. Over the last 25 years I have found that presenting methods and findings using core concepts visually is much more powerful than presenting a lot of technical detail.

Always communicate properly what are all the demands and requirements, it is essential to understand the demands first so that it can save a lot of time

This is essential. The pace of change in the machine learning domain is extremely fast. However, don't embrace change for changes sake. Don't be afraid to utilise existing robust methods that work, if they achieve what is needed. Don't be afraid to evaluate new approaches against the old and carefully consider if something can be gained. So many embrace new methods without carefully considering if they are offering an advantage in the domain they are working in. Just because an approach is trending doesn't mean it is the right one to use.