Welcome back to Beyond The Data! This month, we’re highlighting Mandar Kale, one of our Machine Learning Architects. He’s eager to learn as much as he can, quick to offer his assistance when he can help a coworker, and always does it with a smile.
Tell us your name and where you’re from.
What does "Machine Learning Architect" mean? What do you actually do in any given day?
My title is pretty self-explanatory: I architect machine learning solutions. On any given day, I do one or more of the following tasks:
- Understand client requirements and what problems that they are trying to solve
- Analysis of requirements and comparison with the technology stack that’s available
- Quick POCs, demos, or workshops based on our analysis
- Document and share recommendations about machine learning algorithms, methodologies, and technology stacks that can be used
- Architect and design the best possible solution for clients in the view of data and available technology
Tell us about the Machine Learning Engineering team! What is it like working with them every day?
We really have a great MLE team at phData. Everyone on the team is very passionate about technology and brings in his or her unique experience and expertise, which ranges from BI, big data, data science, and MLOps to specific industry practices like insurance, healthcare, and retail.
We all help each other with great patience and encourage each other to ask for help or share any doubt without second thoughts. This skill mix and collaboration brings great value to the table as we work on client projects.
Interested in working with Mandar?
phData is growing fast and looking to extend our teams!
How long have you been with phData? What past experiences have prepared you for your job at phData?
I have been working with phData for the last two years. I simply love learning and researching new things, and I’ve always focused on designing/developing solutions and research in data mining, machine learning, big data, data warehousing, and BI.
I worked for a few years in the R&D department at my previous employer. When I returned from the U.S. in 2014, I was looking for an organisation where my passion for learning new niche technology and data would be encouraged. One of my friends referred me to phData. After talking with the senior management team at phData, I decided to join the team and I’ve been very happy about that decision.
How have you seen the company change in that time? How has your job evolved?
When I joined phData in 2018, there were 20 employees in India and 60+ in the US. In the last two years, we grew from 80 employees to over 150 As the company grows, things have inevitably changed and we’ve had to develop more structure and processes to ensure sustained growth.
Though phData is growing and all the necessary changes are happening, I see no compromise on our core values and a very clear thought process about our business. I’m very glad to witness, experience, and be part of this evolution.
What is the one thing you want customers to know about phData?
What are the most exciting things you’re working on and how do you see them positively impacting our customers?
I’m currently working on learning and developing on data science frameworks, like Dataiku. These frameworks facilitate self-service AI. They are very future-proof and extensible (plug and play with any other technology stack).
Two of the burning needs of any business that I can see are:
- Engineering ML models to make them work at scale
- IT enablement and operationalisation of ML models (production deployment)
What has your experience working from home been like?
Working from home is tricky. You don’t get a chance to break out with your friends and those small breaks are so effective for reducing stress and increasing productivity. But somehow, I’m used to it now.
One thing that has been essential to my success working from home is having a separate space. You have to create an environment similar to an office, free from noise or other distractions. Thankfully, I created a separate office while constructing my house, but it was still difficult to focus at times this past year since my entire family was home 24 hours a day. I find it is more efficient to work either late at night or very early in the morning, especially if I’m working on something new.
What do you do for fun when you’re not working?
