1.Can we meet you?

My name is Nafisa Lawal Idris, and I am a Data Scientist with over three years of experience based in Nigeria. Currently, I’m driving innovation at Approvam, a B2B solution that streamlines approval workflows. I harness my skills in data analytics, machine learning, and AI-driven solutions to enhance business processes and deliver impactful results. 
My experience spans various industries including SaaS, FinTech, EdTech and IT Solutions. I’m deeply passionate about technology and advocacy, actively promoting diversity and inclusion in the tech industry through my work with organizations like KaggleX, ADPList and Women in Data Science (WiDS).
 

2. Can you walk us through a data science project you’ve worked on that you’re particularly proud of? What challenges did you face, and how did you overcome them?

One project I am particularly proud of is the Market Basket Analysis using the Apriori Algorithm. This project aimed to uncover purchasing patterns by analyzing retail transactional data. By applying the Apriori algorithm, I identified frequently co-purchased items and generated association rules that provided actionable insights into customer behavior. The main challenge was managing the computational complexity, given the large dataset and multiple passes required by the algorithm. I tackled this by employing pruning techniques to reduce candidate item sets and using efficient data structures to enhance performance. Fine-tuning the algorithm’s parameters allowed me to focus on the most significant rules, filtering out noise and irrelevant patterns. This analysis enabled the retail business to optimize inventory, implement targeted promotions, and improve customer satisfaction, demonstrating how data science can transform raw data into valuable business intelligence.
 

3. What inspired you to pursue a career in Data Science?

The drive to make impactful decisions and solve real-world problems through data inspired me. My background in Statistics and Management laid a solid foundation, but it was the potential to leverage data to influence business strategies and outcomes that truly motivated me. The blend of analytical rigor and creative problem-solving in data science captivated me and fueled my commitment to this field.
 

4.How has the program changed your career or life direction?
 

The program has been a game-changer significantly enhancing my technical skills and deepening my understanding of data science methodologies. It provided practical experience with real-world datasets and exposed me to advanced tools and techniques. This has empowered me to tackle more complex projects and make data-driven decisions with confidence, shaping my career and enabling me to take on new challenges with greater expertise.
 

5. How do you approach the task of cleaning and preprocessing data? Can you share a specific technique you find particularly effective?
 

My approach to data cleaning and preprocessing begins with a thorough exploratory data analysis (EDA) to understand the dataset’s structure and identify areas needing attention. I handle missing values with data imputation, normalize or standardize features as needed and address anomalies through outlier detection methods. A technique I find particularly effective is feature engineering. Creating or transforming features enhances the dataset’s relevance and improves model performance. For example, in time-series analysis, I might generate rolling averages or time-based indicators to capture temporal patterns. This ensures that the data reflects underlying relationships and trends, crucial for accurate analysis and decision-making.
 

6. What advice would you give to someone just starting out in data science, especially when it comes to developing essential skills and gaining practical experience?

Start by building a solid foundation in the basics, such as statistics, programming, and data manipulation. Explore practical experience by working on various projects, whether through internships, competitions, or personal projects. Platforms like Kaggle offer valuable opportunities to engage with real-world problems and refine your skills. Stay curious and embrace continuous learning, as the field is always evolving. Networking and seeking mentorship from experienced professionals can provide invaluable insights and accelerate your growth.
 

7. Data science often involves working with large datasets. How do you ensure data accuracy and maintain quality throughout your projects?

Ensuring data accuracy and maintaining quality is critical. I start by validating data sources for reliability and accuracy. During data cleaning and preprocessing, I use automated scripts to detect and correct anomalies and inconsistencies. Regular sanity checks and validation tests throughout the analysis phase help catch errors early. Implementing version control for datasets and rigorous documentation of all modifications further ensures accuracy and quality throughout the project lifecycle.
 

8. How has your experience in the boot camp influenced your approach to solving real-world problems with data?
 

The Utiva Data Science Boot camp was instrumental in shaping my approach to real-world data problems. The comprehensive curriculum provided a robust understanding of data science principles and hands-on practice with diverse datasets. I learned to approach problems methodically, from defining the issue to performing data cleaning, exploratory analysis, and applying advanced techniques. The bootcamp’s emphasis on effective data visualization and storytelling enhanced my ability to communicate insights clearly. The focus on tools like Excel, SQL, Power BI, and Python combined with practical projects reinforced the importance of collaboration, adaptability, and continuous learning, all very important for tackling the dynamic challenges in data science.
 

9. How can our readers connect with you?

I’m always excited to connect with fellow data enthusiasts and advocates. You can find me on LinkedIn Here.

 Feel free to reach out; I’m eager to build a strong network and support others in their journey while embracing new challenges myself.