1, Please introduce yourself, what you do, and your current role.
I am Precious Nnodi, a data analyst with a background in mechanical engineering. I specialise in uncovering trends and anomalies using various business intelligence tools. Currently, I am involved in multiple projects where I apply my expertise in data analysis to extract insights and drive informed decision-making. Additionally, I am interested in pursuing a master’s degree in data science to explore research areas that can be implemented in the field of mechanical engineering.
2, Tell us about your path into data science. What inspired you to pursue a career in this field? Is this what you’ve always wanted to do?
My interest in data science stems from my passion for uncovering patterns and insights that can bring about significant changes in systems and institutions. I realised that by harnessing the power of data, I could not only enhance business strategies and processes but also make a positive impact on society. As someone dedicated to personal and professional growth, I constantly seek opportunities to expand my knowledge and skills in data science and analytics. I actively keep up with new technologies and tools in this rapidly evolving field, as staying at the forefront is crucial for effective growth. I strongly believe in the potential of data-driven insights and algorithms to make a substantial difference in society, and I am always eager to leverage my skills to drive positive change. The transformative power of data, my commitment to continuous improvement, and my desire to contribute to society have been the driving forces behind my journey in data science.
3, What are some of the biggest challenges you have faced on your career journey, and how have you overcome them?
Throughout my career journey, one of the major challenges I faced was acquiring new skills like programming, machine learning, and business intelligence tools as a transitioning student. The abundance of learning materials often led to burnout and feeling overwhelmed. However, I overcame this challenge by seeking guidance from a mentor who provided me with a clear learning pathway. Additionally, I dedicated myself to continuous learning from other professionals in the field. I realised that the implementation of knowledge and problem-solving in real-world scenarios is more important than the mere accumulation of knowledge.
4, What advice would you give to those who are just starting out in AI and data science? What skills or qualities do you think are most important for success in this field?
Success in this field requires a strong foundation in domain knowledge, a commitment to continuous learning, practical experience, analytical skills, effective communication, and building a network of professionals. It’s important to remember that success is not solely dependent on technical skills; adaptability, curiosity, and the ability to collaborate with others are equally crucial. Perseverance will also play a significant role when facing challenges along the way. Data science and AI encompass a wide range of applications across various fields, so it’s important to explore opportunities to implement knowledge from this field in different areas of society.