August 18, 2023

Data Analyst Spotlight: Fibi Dalyop

1. Please introduce yourself, what you do, and your current role.

I’m Fibi Dalyop, a Nigeria-based data analyst and machine learning specialist. I’m currently a data analyst at Women First Digital, an organization dedicated to employing digital technologies and data-driven strategies to tackle issues pertaining to women’s sexual and reproductive health. My skills encompass deciphering user patterns and pinpointing avenues for enhancement. Before this role, I worked with governmental bodies, contributing to the execution of various social protection initiatives through data-centric methodologies.

 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 introduction to data science happened within the realm of social impact. While working with the government, I became aware of the profound role that data can play in shaping and optimizing policies and interventions for social protection. Witnessing the potential of data to drive informed decisions and create positive change within communities inspired me to delve deeper into the field of data science.

The opportunity to harness the power of data to enhance social protection measures and make a tangible difference in people’s lives resonated deeply with me. While I may not have initially set out on this precise path, the realization of data’s pivotal role in shaping social policies solidified my commitment to a career in data science. It’s a journey that has aligned my passion for data-driven insights with a higher purpose of contributing to meaningful social transformation.

 3. What are some of the biggest challenges you have faced on your career journey, and how have you overcome them?

One of the significant challenges I encountered on my career journey was the steep learning curve associated with transitioning into a more data-centric role. As someone who originally came from a different background (Metallurgical and Materials Engineering), I had to immerse myself in learning various programming languages, statistical concepts, and machine learning techniques. Overcoming this hurdle demanded dedication and persistence. I took advantage of online courses, workshops, and mentorship opportunities to rapidly build my skill set. Continuous practice and hands-on projects were instrumental in solidifying my 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?

To those embarking on their journey in AI and data science, my advice would be to cultivate a strong foundation in both technical skills and critical thinking. Begin by mastering the fundamentals of programming languages like Python and R, as they form the backbone of data science and AI development. Embrace continuous learning by enrolling in online courses and participating in coding challenges; Staying curious and open to new methodologies will set you on a path to success.

However, remember that technical prowess is only part of the equation. Equally crucial is the ability to think critically, analyse problems from various angles, and derive actionable insights from data. Additionally, data storytelling—the ability to communicate your findings effectively to non-technical stakeholders—is invaluable. Lastly, cultivate patience and resilience. The journey might present challenges, but each obstacle is an opportunity to learn and grow. Embrace failure as a stepping stone to success, and never underestimate the power of perseverance.