Zulhans Ramadhan Maharoesman— RevoU Instructor | Business Intelligence Analyst Lead at GoPay
Zulhans is skilled in digital strategy, problem-solving, statistical data analysis, and data analytics. He has been working with GoPay for almost three years as the Lead of GoPay Business Intelligence Growth, Closed Loop, and Risk & Fraud Stream.
Zulhans Ramadhan Maharoesman, or usually goes by Zulhan, is an experienced Business Analyst/ Intelligence with a demonstrated history of working in the startup industry. He is skilled in digital strategy, problem-solving, statistical data analysis, and data analytics. He has been working with GoPay for almost three years as the Lead of GoPay Business Intelligence Growth, Closed Loop, and Risk & Fraud Stream.
Being a part of GoPay as an organization makes him very proud since the company focuses on impacting society. He also loves leading his team full of many talented professionals.
His responsibilities at GoPay include but are not limited to:
- Providing customer segmentation based on their personas,
- Doing deep analytics on customer behavior to give strategic insights for businesses to make decisions,
- Doing tactical and strategic analysis and data modeling to answer questions about customer segmentation to improve GoPay key metrics performance.
Has been experienced in data analytics, he believes that there is no such thing as “Investing in data is too expensive.” He thinks that bad data infrastructure and data processing tools will cost companies more.
Not only about technology, but it’s also essential to invest in talent. Zulhans believes that a lack of data analytics talent could harm the organization because they can give you misleading information.
Zulhans will be one of our instructors in RevoU Data Analytics program. Join the program to learn more from Zulhans!
Questions & Answers
#1 Can you explain to us what your typical day looks like in your current role at GoPay?
My typical day to day work as Business Intelligence Analyst Lead at GoPay:
- Meeting, sync, and alignment with stakeholders (business and product teams) about the existing or upcoming projects.
- Meeting, sync, and alignment with the data team across the organization.
- Daily standup with my team. Helping them if there is any blocker.
- Weekly sprint planning (project management). To manage the bandwidth of my team and give clear expectation about the delivery of our tasks to the stakeholders.
- Doing internal Business Intelligence project to improve the process within our team which can bring impact to the organization.
- Create SOP to improve the process of team’s performance (process improvement).
- Strategic thinking and planning. Helping the organization to achieve the OKR.
- Problem solving, both in technical and business aspects.
- Maintain the good quality of our data products, resolvement if there is any escalation.
- Explore the forest of data to get some insights about what’s currently happening in the organization.
- To help finding the ‘why’ of what’s going on with company key metrics performance.
#2 Biggest myths and misconceptions about Data Analytics?
- Fancy data modeling is always better
Using fancy or sophisticated data modeling will not always give you a better result. You can get impactful insights too with just using excel; as long as your insights and recommendation is on point. Meaning, it can solve the business question and meet the objective.
- As data analyst, you spend most of your time in data crunching
This is not effective. To give a more effective data product, you better spend more time on the planning instead of going directly into the execution part. Think strategically what you want to do before the execution. Align with your stakeholders and always start the execution when your problem statement, objective, and/or your hypothesis is already well-stated. Always plan your project mindfully.
- Investing in data is too expensive
Bad data infrastructure and data processing tools will cost you more. Garbage in garbage out. Not only about technology, but also in investing in talent. Lack of data analytics talent could harm the organization because they can give you some misleading information
- Communication skill is not important as data analyst
This is so wrong. As a data analyst, we have to master the skills of communication. Our job is not always behind the desk and querying the data without knowing what we’re going to do with that bunch of data. A good data person should understand the business problem by gathering requirements from the relevant stakeholders. You sometimes have to present your insight by writing a narrative or giving a presentation to the audience.
#3 Your proudest professional achievement at GoPay?
- Being a part of this organization (GoPay) is already my proudest achievement. I’m happy that this organization can bring so much impact to society.
- Leading a team which consists of many talented professionals.
- Giving impact to the companies by using our data products
#4 Things you wish you could have learned earlier in your career?
Start my Data Analytics journey earlier.
#5 Books / Online resources you follow to remain on top of the most important industry trends and keep improving in your field (blogs, podcasts, newsletters)?
- Lean Startup by Eric Ries
- Lean Analytics by Benjamin Yoskovitz and Alistair Croll
- GoFigure podcast
- TED Talks
- Viral Loop by Adam Penenberg
- Learning How to Learn (Coursera) by Barbara Oakley
- The McKinsey Way by Ethan Rasiel
- Storytelling with Data by Cole Nussbaumer
- Startupedia by Anis Uzzaman
#6 Your tips for someone who is interested in starting his career in Data Analytics (aside from applying to RevoU)?
Don’t be afraid to start a career in the Data Analytics field. There is no such thing as the right major/degree to become a data analyst. Always improve yourself and be curious with the data analytics topic. Try to start a data project or join a competition, it will help you to get an upper hand in the recruitment process in the future. Always remember, the best investment is yourself :)
#7 The fundamental skills a Data Analyst is expected to have?
- Logical thinking
- Problem solving
- Mathematic / Statistic
- Critical Thinking
- Communication / Writing
#8 What distinguishes a good Data Analyst from a great one?
A great data analyst is the one who can convert data into action which bring significant impact to the organization.
Learn from Zulhans and other great instructors by applying to RevoU Data Analytics program
Looking to kickstart your career in Data Analytics but don’t know where to start? Apply to RevoU 13-weeks Data Analytics Program
How RevoU works:
✓ Live daily interactive online classes for 13 weeks (7–9pm WIB)
✓ Learn from the best instructors in the industry (such as Zulhans)
✓ Personalised career coaching with 1:1 mentorship sessions
✓ If you are looking for a job and don’t get one at the end of the Program, the entire course is FREE
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