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Behind the Scenes of Advanced Analytics & AI : Q&A with R&D Data Team Lead Smadar Ben David

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As an advanced analytics company, our core capabilities center around data collection, data classification and data management. Our uniqueness comes from our patented NLP and our ability to connect a wide range of unstructured external data sources to surface trends and predictive insights. Behind the scenes is our R&D team, who continually push the boundaries with AI and machine learning.

 

Smadar Ben-David is Signals Analytics R&D Data Team Lead, and we were excited to spend some time with her to delve into some of the more interesting aspects of the data journey and what makes the Signals Analytics approach unique.

 

Tell us a little bit about your role at Signals Analytics and how you got here.

 

I am leading the data team within the Signals Analytics R&D department, working closely with developers making sure we utilize the best and newest technology available and its compatibility to Signals Analytics unique needs.

 

My team of analysts is responsible for the creation of the Signals Analytics product, implementing new technologies, developing new data processing methodologies, source development, pre-sale research and involved in dictating the quality assurance processes and SLAs.

 

I started working at Signals Analytics in 2017 as a pharma analyst, after my graduation from Ben Gurion University where I got my Master’s degree in molecular biology. I was looking for work in an adjacent field that would have allowed me to use my love for biology and let me develop other knowledge and skills such as management and technology.

 

Data science is a field that is highly sought after yet has few women. What do you find attractive about this field and what would you tell other women who may be thinking about pursuing a career in data science?

 

Data in general and data science specifically are indeed very popular these days. As the world entered the golden age of the internet, the use of smart phones and social media upraise has increased our ability to create content and store it. The potential stored in these massive amounts of data is unlimited.

 

I would tell any woman to go for it - it is a new, exciting and wide-open field where you can shine, lead and excel.

 

How does your role help clients fulfill their vision to get from data to insight and be more data-driven?

 

In my role, my team and I are making sure our data is of high quality, containing the most relevant and accurate ways to describe the ecosystems.

 

We continuously strive to have the most relevant data sources and the best algorithms to connect all these disparate data types. This makes our data trustworthy and the gives our clients that ability answer their toughest business questions via our platform with high confidence.

 

What can you tell us about the new data processing technologies that you are implementing and some of the quality assurance methods that you have developed to ensure accurate and clean data?

 

These are exciting times for our data and technological teams as we are incorporating new technologies to allow us to scale up: data volumes, speed of processing, data querying and data quality. We are utilizing machine learning and NLP technologies to improve our classification accuracy and recall and surface meaningful keywords (tokens) so we can be ahead of new trends and early signals.

 

Every quarter we broaden our capabilities, increasing our ability to store and search over more and more data points and scale more processes to generate maximum data processing horsepower. For example, we continue to set the bar higher with data quality and are crossing new thresholds. We have massive QA processes and use cutting-edge classification engines to ensure high-quality data which leads to high-quality insights.

 

How can our clients derive maximum value from their deployments with us? Is there any special skill required?

 

There are no special skills needed to deploy and implement the Signals Analytics platform, however, our system does have many configuration options. In order to get maximum value when approaching the Signals Analytics platform, it is best to narrow down the business question at hand and to be familiar with our data types and taxonomy to ensure optimum results.

 

What do you like most about working at Signals Analytics?

 

The Signals Analytics culture is vast and amazing. I love that there are many community volunteering opportunities, company trips, prize winning contests and so much more.

 

During this difficult time with Coronavirus, we started working from home (and still are). This obviously could have raised many challenges with communication, home-work balance and keeping the team’s sense of unity. Working at Signals Analytics, however, I had no doubt that our great HR team and management are doing all they can to ease this transition; starting with hand delivering spring holiday gifts to all employees, sending flowers to our parents who had been suffering from the prolonged isolation, to delivering computer equipment to create the best working environment each at their own home, it is easy to see that Signals Analytics is composed of amazing people, who are dedicated to the cause. We are developing cutting-edge technology in our field and are improving every day to provide high quality data to our data savvy clients.

 

Where do you think the world of advanced analytics is going next?

 

I think that the better the technology gets, we will see the use of data analytics penetrating more and more ecosystems, eventually touching every aspect of decision-making in an enterprise.

 

We will see new data types being added with a click, and highly adaptive taxonomies and hierarchies grouped into new concepts. We will see image recognition, video analysis and text analysis being combined and connected to extract new information, and this will create new ways to predict and identify early trends. We will have even more informed insight into consumer needs and the market landscape, helping the customers we serve succeed with their business goals.

 

And from the Signals Analytics side, as we deepen our understanding of all these new data sources, how to store, query, and clean them, we too, will be able to adapt our platform and additional use cases we can support.

 

 

Want to take a look under the hood and learn more about the world of advanced analytics? Schedule a demo today!

  

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