Interviewee: Juber Rahman

What job did you get, Juber? 

A Senior Data Scientist Role at FedEx Services, Tennessee, United States.

 

Can you describe your journey into data science? 

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.

 

Can you share a point in your career where things got a bit difficult? And how did you overcome roadblocks? 

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 of the 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 portfolio. 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 that helped me to develop a good understanding of the related tools/ methods. It also enriched my portfolio a lot. 

 

How did the Omdena experience help you in securing the job? What tips would you give to current Omdena collaborators?

I would like to focus on two specific points that most of the employers / hiring managers I had an interview with admired:

  • Developing a solution from scratch. You don’t have a well-defined problem, no curated dataset, even the research community does not have a well-accepted solution to the problem. Next, you develop a working prototype of the solution or more in only 8 weeks. You collect data, process, and annotate the data, and finally develop a classification/regression model. This is a skill very much needed in the industry setup.
  • Collaboration and teamwork. In Omdena projects you collaborate with others, attend group meetings, accept the differences in opinions, and provide constructive feedback. You learn how to motivate others to achieve the goal. 

 

I would suggest that Omdena collaborators take a challenging responsibility willingly e.g. task manager, accept constructive criticism, 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 the hiring managers. Finally, update your GitHub and LinkedIn with Omdena project experience.

 

What role does your Ph.D. play in your career? 

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 the problem. This includes conducting a literature review, pursuing a novel method instead of re-inventing the wheel, evaluating your solution. And finally documenting the solution in a standard manner. 

 

What was the best advice you got from someone in Data Science? 

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.

 

Any closing words?

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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