From IT Project Management to Data Science, Here is How Sairaman Ramasubramanian Transitioned His Career in 3 Months

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In June 2021, Sairaman reached out to us with a strong interest in our full-time Data Science & AI July program. After strong consideration, he took a leap of faith and quit his full-time work, pursuing our course with intensity and focus. Having multiple qualifications under his belt and quite a successful project management career in this area, he still saw the great need to upskill in Data Science. His strong interest lies in branching his career out into Cognitive and Artificial Intelligence, where he can effectively use Machine Learning. 

3 months was all he needed to upskill, adopt the most in-demand technical skills, and secure work placement. He now works for Deloitte Consulting as a Manager in their Data Science & AI department. His journey is very inspiring and showcases how we support our students in their career transition. Have a read of his story with us here:

Can you describe your career experience before making the change to data science & AI? 

“I did my Bachelor’s degree in electrical engineering from India and started working as a Systems Analyst in Mumbai, working on Oracle PLSQL, Forms3.0 and Unix. After about a year and a half, I got an opportunity in Singapore and I have been working in Singapore since 1998. I started off as an Analyst Programmer and have worked for Big 4 consulting firms, blue-chip IT companies and Top banks in various capacities focusing on the data side of things. I have been involved in the conception, architecture, design and delivery of end-to-end Data warehouses and data marts for multiple financial organizations.

I did my PMP certification and for the last 12 years have been working in the capacity of a Project Manager Delivering Data Warehouse / Marts in the areas of Risk & Regulatory reporting for Banks.”

How did you transfer and apply your previous career experiences to better prepare you to study data science?

My extensive experience in different projects in the financial services sector in the areas of Data analysis, SQL query and performance tuning as well as Project management helped me to approach Data science in its entirety as in understanding the entire data life cycle etc.”

What were your career goals before upskilling to data? How has your outlook changed?  

“My Career goal was to branch to the Cognitive & AI space to effectively utilise ML models as well as pick up on Python etc. which the course really equipped me with.”

Why did you choose to join the Full-Time Program in particular? What appealed to you?

“I had a few constraints on the personal side of things which I wanted to take care of and given the rigour and demand of work as well as the course curriculum, I thought it would be better to go for a full-time course as that would mean I can take care of my personal constraints and need to focus only on studying. So, by God’s grace, I have been able to somehow manage both.”

You’re now working with Deloitte Consulting as a Data & AI Manager – Congratulations! How did you get a job in the industry after completing your training and what guidance would you give someone applying for jobs after upskilling?

“I started applying towards the tail end of the course. It was a 12-month course and I started applying after week 10. I did get a few calls immediately.  LinkedIn Premium really helped me to reach out to a lot of positions. While some roles were looking for more experience in Python and cloud, some moved ahead. I was lucky to be interviewing at 3 places and Deloitte closed in first and is one of the best names in the industry and role was within the Cognitive AI & Data Practice, I chose to move ahead with that.

I would advise candidates to have a good resume which I should thank IOD for the format and be candid & open about “what you know and what you don’t know”.

Need to be as much honest, clear, concise and to the point as much as possible.”

Tell us about your current data science role, what does your day to day involve? What tools, techniques and processes do you use?

“Currently, I’m managing a team working on some components of AWS, Python and Pyspark for an Insurance client. We are in the SIT stage and day to work involves defects tracking, allocation, team management and status reporting.”

How do you compare your career situation now to 6-12 months ago?

“It’s much better by God’s grace. I’m working in my area of interest and that too with a top consulting firm which really makes me happy.”

Would you recommend upskilling to fellow professionals? Who would be suited to become trained in data in your opinion?

“Yes, I would recommend upskilling as it gives a chance to get aligned to the latest in the field. In some cases, depending on the passion, it could be cross-skilling as well. But I would recommend everyone to do some introspection and have some goals. 

In terms of getting trained in data, I feel anyone who has a passion and loves number crunching and has attention to detail, would be fit for training in data. A background in Math & Statistics would help but is not a necessity. Industry experience is good enough, especially for the people who have worked for a long time in excel with number-crunching etc should be good candidates.”

Tell us about your capstone project! How did you come up with your topic?

“My capstone was on Sentiment Analysis on IMDB database (NLP + Classifiers). I worked together with my Trainer in shortlisting and finally selecting this project.”

What did you enjoy the most about the capstone project?

“It allowed me to put to use all concepts & most of the models that I had studied in the course as in doing an entire NLP pipeline, feature selection, build different ML Classifier models, train & finally predict the sentiment.”

What would you say was your biggest learning or take away from the process of completing your capstone project?

“The biggest takeaway was the coverage and rigour of the capstone project as it involved putting in to use soft skills like Planning, time management etc. in addition to the technical aspects. Lastly, the presentation and feedback session were quite useful.”

What guidance would you give someone from a non-IT background that wants to upskill to data science?  

“I would recommend them to do the Data camp re-requisites quite diligently like python programming and, if possible, brush the Math and statistical concepts as the course is rigorous in those aspects. The most important aspect is the analytical skills.”

Connect with Sairaman on LinkedIn.

If you are interested in up-skilling and transitioning your career to the Data Science field in Singapore, schedule a consultation with a Data Industry Career Consultant today.

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