It seems like everywhere you look, more and more devices are connected to the Internet. All of those “smart products” and their billions of bytes create “Big Data.” Making sense of all that data and knowing what to do with it is a big challenge. So it’s no surprise that data science has been identified as a top skill to have.
For data scientists at Honeywell, it’s a way of making the world a
Here's what it's like to spend a day with them:
Atul Katole, Senior Scientist, Bangalore, India
9 a.m. I help security cameras identify and categorize objects in images as dangerous or not, using machine learning algorithms. I’m imagining a future where security and surveillance cameras can recognize people wearing masks, carrying guns or sharp objects and then raise an alarm. Machine learning is helping devices such as security cameras learn on their own to do things only humans were capable of before. Smart surveillance will make our world safer.
Noon I review, design and adjust machine learning models for video analytics, object recognition, text analytics, speech and audio recognition used in building surveillance to ensure it runs smoothly. It’s all about building intelligence into security devices in your homes and offices using machine learning.
4 p.m. Most of my time is spent reading academic papers and technical publications. Our challenge is to turn the unknown into actionable insights by using data, so it’s important to be curious and learn as much as possible.
9 p.m. I watch TV with my family and read a story on Indian mythology to my children.
Words of wisdom for Data Science practitioners: Always work on problems that truly matter and that you’re passionate about. Too often, we find ourselves pursuing goals we don't believe in, and this will only lead to failure.
Raman Samusevich, Research Engineer, Prague, Czech Republic
9 a.m. I begin the day by developing machine learning models that teaches devices in a home to auto adjust their settings just like how a homeowner would. Machine learning is the future of a connected home. It can create an environment that learns from a homeowner’s interaction with devices to bring them better comfort when they are away.
Noon I design and tune machine learning models to evaluate its performance. As data scientists, we typically sort through a whole range of data parameters to get these models right. I then visualize patterns in data generated by connected devices to reach new insights in bringing comfort to homeowners.
4 p.m. I check on several blogs, websites and Kaggle forums to understand what others are doing in data science.
9 p.m. I like to go for a swim, read a book or watch a movie.
Words of wisdom for Data Science practitioners: Spend time with data and get your hands dirty. You’ll invariably learn something new. You must be curious and a constant learner to make discoveries in the world of big data.
If you’re interested in working in the world of data science machine learning, apply here.