Here's how you can advance your career in data science through assertiveness.

You have to be vocal about your ideas, but the confidence comes after extensive research, reading and experimenting, have extensive research and do all possible researchs and what can be shortcoming remove all these, that will give you better conviction, also get ready to handle criticism, it will not be always constructive, but be furious untill it is not hindering your work. Work hard and party harder.

Early in my data science career, shyness held me back from voicing my ideas. But I learned a crucial lesson that the data insights are only valuable if communicated effectively. Data professionals have a responsibility to uncover hidden insights from data, not just passively analyze it. Assertiveness allows you to present your findings clearly and confidently, leading to greater impact on business decisions. Emphasize that voicing your ideas isn't about self-promotion, but about contributing to business growth. Your innovative ideas can lead to new perspectives that solve problems or create opportunities. Don't shy away from presenting even seemingly small ideas. Every contribution adds value and can lead to bigger things.

To advance your career in data science through assertiveness, focus on proactive communication, taking ownership of projects, seeking opportunities for growth, and confidently advocating for your ideas and contributions.

Masters never hegitate to get feedback from others, if you feel shy that means you need to do more in that, A feedback is a method of getting raw perspective, If you want diversity in feedback, you ask to interns, associates, seniors, and Tech leads, they all will give you different thoughts which will save your hours and especially reduces the bias that we almost, when we are building, It is easy to dig out others error than owerselves. Even people appreciate when you take their feedback, in corporate it is one of the double win method through which you can make your coleauges feel special as you are taking their suggestion. You can ask to any non IT guy too, if it is very sensitive and can be solving millions of people's problem.

Assertiveness in data science entails not only sharing your ideas but also embracing feedback. In a field marked by constant evolution, feedback is a catalyst for growth. Soliciting input from colleagues and mentors demonstrates respect for their expertise and a dedication to learning. It fosters collaboration, unveiling opportunities that might otherwise be overlooked.

Mentorship will be always a pivotal point in Data Science, If you are seeking mentorship, Think yourself like a company and hire board members that are top notch mentors who will guide you to be the one you want to be. Surround yourself with the people whome you like to be or who may have collective quality you want to have. If you are mentoring then this will be helping you to clear your concepts, and keep remembering the facts, also indirectly you are helping someone, It's a good social cause as well, Give back to society, from where you came, to the world.

In my journey as a data scientist, I’ve found that continuous learning is an essential aspect of career advancement. The field of data science is ever-evolving, with new techniques, algorithms, and tools emerging regularly. Staying updated with these changes is crucial. I dedicate a portion of my time each week to learn something new, be it a programming language, a machine learning algorithm, or a statistical method. This habit not only enhances my skill set but also keeps me engaged and passionate about my work. Remember, in the world of data science, learning never stops!

Leaders in data science, in my opinion, need to be lifelong learners as well as leaders. Agile leaders promote innovation by keeping abreast of market developments. Recall that assertiveness and continuous improvement go hand in hand in good leadership.

Project leadership is a milestone in your career, this may be not started big, if you start taking ownership of your task it is good to start, though Data science is a very big domain, and there are multiple roles in that but come forward and take responsibility, you will have to fight, this is war, and survival of the fitest is the ultimate, here fitest has nothing to do with survival, whatever you are you have to win, but remember don't think about someone's defeate, only focus on your win, If you are winning that doesn't mean someone is loosing, world is not binary, Focus on your betterment, keep consuming what the top notch people of your industry doning, how they do?, How they behave and How they present and tell the story.

Above all these learning, mentoring, feedbacks. The one thing that is compulsary ingradient is you should be professional in whole journey, In reallife the feedback are not always constructive, get ready for the worst, There are always good people and toxic people in both in corporates. You listen everyone, but when you reply, please be very careful, because world only remembers answers of the legends, If you wish to be legend of your field, Your respectful, humble and cool attitude will build your personal brand and industry knows and rates people, don't think you are nowhere in the ocean, Everything is getting recorded, so express like this is forever.