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How To Become A Data Scientist In Nigeria (2022)

Data Science is renowned as one of the most valuable careers now and a lot of people are jumping on to its wagon. If you have plans of becoming a data scientist in Nigeria, you’re on the right page. Check out the 8 steps to becoming a data scientist in Nigeria below: 

  1. Get Background Knowledge 

While it is possible to become a Data Scientist without prior data-related work experience, you will need to establish the necessary background. A Data Scientist is a high-level post; you should have a broad background in a related discipline before applying. For example, some Data Scientists began in mathematics, statistics, and computer science. 

But whatever field you start with, incorporate Python, SQL, and Excel. These skills are required to organize and manipulate raw data. It also helps to be familiar with Tableau, a tool for creating visuals. Keep a lookout for opportunities to think like a Data Scientist; the more you can deal with data, the better.

  1. Know The Fundamentals

A data science school or bootcamp can help introduce you to the world of data. There are many of these online and in top Nigerian cities. To understand the basics of data science, you’ll need to know how to collect data, analyze it, model it, display it, and present it using tools like Tableau and PowerBI. 

With Python and R, you can develop models that study behavior and predict unknowns, and repackage data into user-friendly forms. Many Data Science job listings state that advanced degrees are required. However, that’s not always possible, but as demand outstrips supply, the proof is in the pudding. Your capacity to demonstrate mastery of the subject is crucial to recruiting managers. 

  1. Master the required programming languages 

Data Scientists use specialized tools and algorithms for data cleansing, analysis, and modeling. Data Scientists should be familiar with statistical programming languages like Python, R, or Hive, as well as query languages like SQL. 

RStudio Server is a server-based development environment for R. The popular open-source Jupyter Notebook includes statistical modeling, data visualization, and machine learning features. Machine learning is a growing part of data science, allowing systems to learn and improve without being explicitly programmed. 

The technologies used for machine learning vary depending on the application, such as training the computer to recognize photographs or extracting trends from social media posts., TensorFlow, Apache Mahout, and Accord.Net are among the technologies available to Data Scientists.

  1. Practice on real-life projects 

Start putting your newly gained talents to use, practicing and refining them. Apply Excel and SQL to manage databases, use Python and R to analyze data using statistical approaches, develop models to evaluate behavior and uncover new insights and use statistical analysis to predict unknowns. 

Try to practice multiple steps of the process, starting with basic company or market research, then defining and gathering the relevant data for the job, cleaning and testing it to maximize its utility. This data can then be packaged into easy-to-read graphics or dashboards that allow people to interact with and query it in a clear manner. Even practicing presenting to others might help your communication abilities. 

Work with text, structured data, photos, audio, and video. Every sector uses data to help leaders make better decisions. If you’re a newbie building your skillset, you’ll want to know the principles of as many types as feasible. Taking on more difficult tasks will allow you to learn more about data usage. 

With descriptive analytics, you may look for patterns in data and use more advanced statistical approaches like data mining, predictive modeling and machine learning to forecast future events or even make recommendations.

  1. Practice developing and presenting data visualizations 

Build your own visualizations from scratch using tools like Tableau, PowerBI, Bokeh, Plotly, or Infogram. Although the core idea behind spreadsheets is simple – producing calculations or graphs by correlating data in their cells – Excel has remained tremendously helpful for over 30 years and is nearly inevitable in data research. 

But gorgeous visualizations are just the start. As a Data Scientist, you must also be able to deliver your findings live to an audience. You may be inherently gifted in certain areas, but anyone can learn them with work. Begin small, presenting to a single friend or family, before going on to a group.

  1. Set up a portfolio 

After you’ve done your homework, trained, and built an excellent portfolio of projects, it’s time to show off your skills and land your ideal job. In fact, your portfolio may be the key to your employment search. Consider using GitHub instead of – or in addition to – your own website when applying for a Data Scientist post. 

There aren’t many jobs in Nigeria and your best bet as a data scientist is to get remote jobs from foreign clients.GitHub allows you to effortlessly share your work and results while raising your presence in a network. Because data science is a vast field, there are numerous ways to tackle an issue and many approaches you can bring to the table. 

Provide a captivating narrative and show the employer the difficulties you’re trying to solve. GitHub shows your code in context, making it easier to understand. Don’t include your entire portfolio when applying for a single position. 

Highlight just a few things that best demonstrate your variety of talents across the data science process – starting with a basic data set, defining an issue, cleaning up, constructing a model, and finally finding a solution.

  1. Promote yourself and your skills 

A well-done solo project might be a terrific approach to impress potential employers. Pick a topic that interests you, pose a question about it, then try to answer it using data. As stated above, you should also explore GitHub. 

Document your journey and showcase your findings visually, explaining your method and showcasing your technical expertise and creativity. To ensure an employer knows your merit, your data should be complemented by an engaging story that highlights your problem-solving method and inventive steps. 

Joining an online data science network like Kaggle is another wonderful method to participate with the community, demonstrate your skills as an aspiring Data Scientist, and expand your knowledge and reach.

  1. Apply For Jobs 

Data science has numerous job opportunities. After learning the fundamental abilities, people often specialize in subfields like Data Engineers, Data Analysts, or Machine Learning Engineers. 

It’s possible to get work as a data scientist in Nigeria, for a company or organization. However, and as mentioned before, your best bet is foreign clients. Try to use websites like Upwork and Fiverr to find jobs.