Lucky Joseph was born and raised in the North Central region of Nigeria. He is one of the first few data analysts and scientists in Nigeria that are making changes and advancing the emerging Data digital industry in Nigeria. Lucky loves to dance, play football, and train young minds to learn digital technology skills! He enjoys travelling and spending time with his family. Lucky has an active social life and loves going to music festivals and attending digital technological events in Nigeria. When he is not socialising, you will find Lucky writing computer codes, trying to solve a problem using technology, and teaching people how to write computer codes or how to use various digital technology sector software. Lucky Joseph also loves reading and is also the developer of one of the biggest Rave in the North Central region digital payment system, Debankys POS agent, that almost every business use today in this region.
You’re a data analyst and scientist at Debankys Limited, how long have you been with the company and what have you been doing?
Thanks for having me. I joined this company immediately after my first degree, and I have been with the company for more than a year now. So, in 2019 a friend invited me to a Data Science network event with a company called TheDataLab, after the networking session, I joined their virtual internship programme, and it wasn’t even up to 6 months I started educating youth where I was serving on the importance of data science and AI and the way we can change lives by transforming the way we use data. During this period, I applied to Debankys Limited and got the FinTech’s web developer and Information Technology Analyst position. My day-to-day activity with Debankys Limited involves analysing data for actionable insight, developing its website and applications, and creating and maintaining the company’s digital products.
- Give HND holders a breathing space
- HND graduates have no requisite qualification to be licensed Architects – ARCON president
Explain in simple terms how data science works?
In very simple terms, data science is the process of analysing data to achieve actionable insights. Within an organisation such as yours, data science can be used for a variety of different reasons, but its primary goal in my opinion, should be to find solutions to data-analytics problems that present the greatest opportunities for commercial development and growth, be it in any industry. To explain this, my job would be to determine correct data sets and variables and also collect large sets of both structured and unstructured data from varying sources and then use it to find useful insights and also solve difficult problems for my company.
From your perspective, what should data scientists and businesses expect from 2021?
Data practitioners are part of an extremely interesting industry, yet very fast-paced and complicated. One of the biggest challenges in data science is the data itself. Whatever people resources and a variety of methods might be in place, the data quality is the first and foremost ingredient for a successful data solution.
We as Data analysts and scientists need to, first of all, understand that we have good quality data before we invest in complex implementations; knowing the data and its limitations should be our utmost priority. To overcome data complexities as a whole, we should be in tune with the business side from our perspective and ask what data scientists and businesses should expect from 2021.
Aside from the data, data scientists should manage the quantity of specialisations that are coming up in the business. As a somewhat new and simultaneously huge field, data science has yet to have clear limits between various jobs inside it.
Various specialisations emerge and professionals entering the field have the complex task of tracking down their own place; it is vital to recall, however that overthinking about picking a specialisation and getting your hands on the tools and devices isn’t always a good way forward. Data analysts and scientists
should be flexible and think about their vision and the vision of the business they represent to meet the overall set objectives.
How can people prepare themselves for these changes and challenges?
Each and every individual who is engaged with data science projects ought to remain versatile to what the Future brings. The two people and associations ought to
see things with a bare eye and develop their capacity to focus on the bigger picture of a problem. In spite of the fact that specialisation is the concentrate at this moment, this can’t tackle the bigger issue really more
often than not. I also believe that individuals in this career path should be on top of their game, share resources, communicate between the various parts and discoveries during their processes and also, participate in various data science challenges.
Looking at the challenges of managing remote teams, with the data science industry benefiting the most from work from anywhere. What’s your advice for managing remote teams?
Yes, the normal working regime has moved to remote working because of the pandemic. This has set out open doors for companies and people generally. Many organisations have opened up their applicant pool, and data experts now have more offers that are not restricted to their local network. In the future, this will be the new norm, with a typical; working way of life, pay, connections with colleagues, in social events – I believe that living will change in light of this. Industries and companies will adjust to this new normal, many things will change, and at the same time, they will overcome the challenges in due time.
By default, managing people is a very challenging task, let alone managing in a remote setting. There are various points that need attention by the managers, in that case, some of which are organising everyday tasks, having conversations about peoples’ personal career objectives, and thinking about each person’s personality. For the former, I think it is crucial to put processes together to ensure there is a smooth collaboration where everyone feels happy and included. Work and tasks should be communicated in a preferred way to ensure everyone is up to speed.
It is a tricky one because managers should both give the team space and trust them while showing they support them in whatever they are trying to achieve. For their career objectives, it is also important not to neglect them in an online environment. Being in the office facilitated conversations and networking, but this became harder with remote working. Managers should be much more engaged with the team members to make sure they are still aligned with their future path and encourage them to progress. What should not be forgotten in this situation is the personality of people. For example, managers should consider how they work with introverted and extroverted people and accommodate their needs.
In any case, there is no unique recipe to be successful at this; everyone should be open to experimenting with different models and processes.
What are your tips for new data scientists joining remote teams and companies?
Beginning a new position completely remotely particularly if it’s your first job can be really challenging. First of all, when working remotely, it isn’t easy to familiarise yourself with the company’s policies because you will certainly miss the normal informal chat, discussion and the atmosphere in a typical physical office. Nonetheless, I accept that in those cases, the central issue is to be proactive; I’d propose new data scientists to discuss continually with their partners, participating in discussions about their work and the next steps in a particular project.
Asking questions and sharing results early can also be a catalyst to a good remote working collaboration, minimising mistakes that can arise from absence of communication. Also, it is essential to be deliberate about catching up with your colleagues or wider team, even if it feels unnecessary in the beginning. As the office doesn’t exist with the format we knew, we need to recreate conversations the way we had them before. At the end of the day though, it’s a new situation, and all of us are learning along the way.
What has been your major achievement and impact since joining the company?
Professionally, I’m proud of how far I’ve gone in a few years, from having no knowledge of natural language processing to developing an NLP-based application for my first project as a data scientist. The goal was to create a tool that would automatically moderate the comments section of one of the biggest social network forums in Nigeria (which receives more than a hundred thousand comments per week) and flag offensive words and phrases for the human moderators. It is a brilliant piece of tech that makes the internet a safer, less fuming place while saving many hours of human moderator time.
Debankys POS agent is one of the inventions I developed for the fintech that I am really proud of today because of its impact not just on the business but to members of the public using the POS agent to grow their business and create employment for themselves. Debankys POS agent digital product allows businesses to receive payment for goods and services contactless by swiping any bank ATM Cards or Debankys membership card for payment.
Thousands of businesses and members of the public in North Central region of Nigeria are already buying into this product, with many people setting up pay points where they use Debankys POS agent digital product for banking agency service.
Debankys POS agent product has gone ahead to create employment for thousands of people in North Central region of Nigeria communities using Debankys POS agent banking for agency banking services.
Being able to work with not for profit organisation like Global Peace Development (GPD) in a well-structured and defined environment to train people on different digital skills is also one of my greatest achievements because in the end, we need minds like this that have received ample training to help build the digital sector and the world we dream of everyday.
Diversity and Inclusion are, rightfully, taking their place as part of the wider conversation around the industry. How can we make data science more diverse and inclusive?
Diversity and Inclusion is not a big topic in our continent, Africa, like in the western world. At the same time, I think it’s pertinent for businesses whose products and services are kind of based around data science to understand how thoughtful they should be about their strategy, not only because they should give priority to diverse groups of people but also they should be able to consider the positive impact and benefit this would bring to them in the long run. When building a new product or service that speaks to a wide audience, having employed people with different skills and from different backgrounds can only lead to a more complete product. Especially when it comes to data related, this need is even more emerging because data is complex; it can be interpreted and used in different ways.
Data science Teams always need members with various experiences and skill sets in order for data scientists to address problems effectively. We must promote an office environment that is genuinely open and supportive.
What are your plans for the Future in data science?
Even though I enjoyed working with the company I am with now, I enjoyed working with the team, and I would love to continue, but at this point, I want to further my education. I want to acquire more skills, Industry specific skills to tackle some of the challenges we are facing as a nation in relation to data science and artificial Intelligence. I have secured admission to the University of Hull to study for a master’s degree in Artificial Intelligence and Data Science to advance myself in the field of AI and data science. My future plan right now is to continue pushing myself in this sector and be able to use Data Science and Artificial Intelligence to transform how business is being conducted and improve the global health sector. Data Science and Artificial Intelligence are changing how the health sector operates for the better. I intend to be among those who will create life-saving inventions using Data Science and Artificial Intelligence for a better healthcare system.
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