Our Data Scientist, Harish Biruduganti talks about his experience working at Tech Vedika.
Data Science is an ever-evolving industry. Ask prominent Data Scientists and industry experts, they would say that an Analytics aspirant needs to be constantly updated about the industry. Be it the programming languages involved in Analytics, the industry’s functioning and recruitment process, the tools used, the advancements in its allied fields like IoT, Machine Learning and more, there’s a lot happening in Analytics.
Data Science achieves three significant results:
- Discovery (what we see)
- Insights (what we learn)
- Innovation (what we implement)
In the era of Big Data, storage limitation was solved by the Hadoop framework, but to process the stored data was a challenging task. To give an example, as a Data Scientist, I have been working on the problems related to Image and Signal Processing, where the data was in an unstructured format. To process this kind of data we have to do a lot of learning which covers three areas:
- Machine Learning/Deep Learning
- Statistical Research
- Data/Image/Video/Signal Processing
This leads to retaining a perpetual beginner’s mind because regardless of how much you develop as a Data Scientist, there will be some areas that you could learn and study. One of the things I really enjoy as a part of my work is that the type of work I do varies every week. The dynamic nature of my work allows me to stay engaged in the business.
A Data Scientist is also one of the few people in the organization who knows data better than anyone else. With the current hype around Machine Learning, companies are starting to see data as a huge source of strategic advantage and hence, a Data Scientist is increasingly seen as a vital part of an Organization’s success.
Being a Data Scientist at Tech Vedika, I have been working on different product areas like Biomedical Image Processing (Cardiovascular MRI), Optical Image Processing (Visiting Card OCR), PDF to Excel OCR and development of Face Processing and Tracking algorithms.
The list of frameworks and technologies used in our development are C, C++, Python, MATLAB, OpenCV and Machine Learning frameworks like Tensorflow, Keras, Caffe and NLP. Some of the Deep learning algorithms like SSD, YOLO-v3, SegNet, VGG-16, FCN’s, ResNet and Deep Sense.
As Data Science is a research-oriented area, an AI-based company like Tech Vedika provides its associates to work on various problem statements which are into different domains and build innovative ideas which are beneficial on both the ends.
Interested people can send your resumes to firstname.lastname@example.org to join our amazing pool of Data Science team!