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Interviewee: Juber Rahman
A Senior Data Scientist Role at FedEx Services, Tennessee, United States.
My journey in data science started back in 2016 when I started working for a National Science Foundation-funded project on Smart and Connected Health. It was aimed at disease detection using body-worn sensor data with on-device machine learning. I took some graduate courses on machine learning and AI to get familiar with the topic and fell in love with data science.
After a few years in data science, I realized that to be a good data scientist it is not enough to work with structured data only. Most real-world problems involve image data or text data. So I had to gain mastery of NLP or Computer Vision. Unfortunately, my research group does not work with image processing or natural language processing. I took some online courses but the course projects were too limited in scope to be added to my portfolio. Moreover, thousands of other people have the same projects in their portfolios. This is when I came to know about Omdena and was pretty amazed by the problems Omdena is trying to solve. I worked on NLP and CV projects at Omdena which helped me to develop a good understanding of the related tools/ methods. It also enriched my portfolio a lot.
I would like to focus on two specific points that most of the employers / hiring managers I had an interviewed with admired:
I would suggest that Omdena collaborators take a challenging responsibility willingly e.g. task manager, accept constructive criticism, and prioritize collaboration over competition. To make the best out of this experience, it is important to deploy the model by developing a software tool, application, dashboard, and more. Keep in mind that the expertise to deploy a machine learning model is highly valued by hiring managers. Finally, update your GitHub and LinkedIn with Omdena project experience.
The main contribution of my Ph.D. is the development of my problem-solving capacity. It is very important for a data scientist to understand the problem and pick the right tool/ method to solve it. During my Ph.D. I have learned how to take a systematic and logical approach to develop a solution to a problem. This includes conducting a literature review, pursuing a novel method instead of re-inventing the wheel and evaluating your solution. And finally documenting the solution in a standard manner.
To learn basic software engineering in parallel to machine learning. The job of a data scientist includes a lot more skills other than model development. For example, a good understanding of data pipelines, database systems, cloud frameworks, and object-oriented programming.
I encourage everybody to get involved in Omdena projects. You get the opportunity to impact lives, develop solutions to keep children safe, protect the environment, improve emergency management, and much more. Also, you make friends around the world and above all uplift AI for Good. Thanks, Juber, and all the best in our Senior Data Scientist Job, may we see you in many more Omdena Projects.

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