Data-Driven Culture: Here’s How Dataspark, Hypotenuse AI, and Synthesis Do It


4 Data-Driven Culture Questions to Ask Companies During Interviews

If being in a company that is Data-Driven is a must-have for you, here are some questions you should ask during an interview.

  • How many A/B tests are ongoing at any one time?
  • How is data used to guide product roadmaps and growth experiments?
  • How closely do engineers work with the data team?
  • What are tools used for A/B testings, dashboard, metrics, and analysis?

What to look out for in the answers:

  • Data heavily guide decision-making, and in the DNA of the team

Three Examples of Data-Driven Companies

A data-driven company utilises data insights to find new business possibilities, provide better customer service, increase sales, and more. According to a PwC blog post, data-driven businesses can outperform their rivals by 6% in profitability and 5% in productivity.

Nearly every organization has a key objective of becoming more data-driven, but few ever achieve this elusive position. The following list includes three instances of businesses that are genuinely data-driven.


DataSpark are leaders in processing large geospatial temporal mobility data to deliver intelligence on people and places using the highest data privacy standards.

Source: DataSpark's LinkedIn page

Here's how DataSpark describe their Data-Driven culture:

We measure how our product is used by our user journeys, keeping metrics to identify hot spots that may hurt customer adoption or long-term use. 

We also measure the traffic trends that inform our compute choices for maximising uptime while balancing costs to serve. We also look at performance benchmarking which will shed light on ways to further improve the experience of our data-centric products.

One example is our Data-as-a-Service (DaaS) API product providing a deep analysis of movement data from telco signals. We analyze the query patterns/depth, time periods of those deep calls, geo-location of customers making the calls, the associated response times etc. Doing so allows us to make the best trade-offs between geofencing, spot versus on-demand compute instances on what time of a day to minimize costs, proactively conveying SLAs degradation to customers etc.

Another example is our home-built Data Quality Framework (DQF) which we have now leveraged as part of our CI/CD to ensure all modules in the data processing pipeline are subject to automated data tests. The DQF allowed us to improve our test quality while concurrently correlating how many gaps we still have when our logic meets real customer-provided datasets. This creates a positive feedback loop which drives the engineers to look for areas of improvement.

This year, we also intend to introduce tools to measure our software delivery performance by tracking cycle-time, deployment frequency, change failure rate, and mean-time-to-restore (the DORA golden signals).  This will allow us to know where which part of our internal processes can be further improved.

👉 View the other Culture Codes of DataSpark 

Hypotenuse AI

Hypotenuse is a YC-backed company that uses AI to write content, including product descriptions, blog articles and advertising captions. They take what takes weeks to do, and turn it into days.

Source: Hypotenuse AI's LinkedIn page

Here's how Hypotenuse AI describe their Data-Driven culture:

Hypotenuse AI adopts a data-driven approach for everything. From running Google Ads campaigns to breaking down user profiles, we use tools such as Amplitude and Google Analytics to track our performance. This guides our decision-making process - every step of the way. Why? In start-ups, speed is paramount. Having a data-driven culture allows us to change directions and execute new ideas faster. Tracking information makes it easier for us to make continuous, incremental changes and improvements. 

For example, we conduct A/B testing on our outbound sales emails and track which email headers have the best open rate, which content templates have the highest reply rate etc. We then make tweaks to this every week to optimise callbacks. Constantly looking into ways to improve, we hold weekly team meetings to review key metrics and brainstorm better approaches.

👉 View the other Culture Codes of Hypotenuse A

More: View the list of other Y Combinator (YC) Tech Companies in Singapore


Synthesis unlocks the power of open data. They build original datasets that can detect shifts in consumer preferences and identify growth audiences for their partners.

Here's how Synthesis describe their Data-Driven culture:

Data is at the core of what we do. Every insight and deliverable going out is based on data, which we extract from any type of publicly available resource.

To deliver on this, our team consists of ~50% of Data Scientists; who work directly with the rest of the business (across product and infrastructure engineering and strategy)

👉 View the other Culture Codes of Synthesis

Exploring New Opportunities? Here's More Resources:

How Can I Know if I Am Underpaid?

So, you are a software engineer. Congrats! Your skills are in high demand and your salary reflects that. As more and more businesses require software engineer expertise, you can expect to see your salaries continue to increase.

But how do you know if you are underpaid?

Or how do you know you are not being lowballed for your new offer that just came in?

You can check out how much your fellow software engineers are actually getting paid on NodeFlair Salaries. It is a community-contributed salary data, verified with documents, such as payslips and offer letters. Within a few months since its launch, it already has the largest pool of verified and trustworthy tech salary data in Singapore.

To Employers: Stop Losing Your Next Great Hires!

You might be thinking: “We checked all the boxes above, but why do we still face great difficulties hiring?”

The truth is, there are many other similar companies out there like you that checked all the boxes above.

The issue lies not in tech talents not knowing who you are, but them not knowing about your engineering culture and WHY they should join you.

In addition, you may be spending your job advertising dollars on traditional job boards. However, these job boards only attract active job seekers that comprise only a third of the talent market. Most importantly, top talents are mostly passive - you are casting your net in the wrong sea!

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