We are looking for a Sales Development Representative (SDR). Remote.
We are a team of 18 people. We develop software for people who studied business, economics, biology, engineering, journalism... to enable them to do advanced data analytics without knowing how to write code. For those creative people that find Excel and current business intelligence tools (like Tableau or Power BI) too limited .
We allow them to run analyses that are more "predictive" and "prescriptive" than descriptive, with the same power of analysis as if they had studied Maths or Computer Science and they knew how to write code in Python or R... for more than 50 different use cases that we have identified so far... from developing new drugs, to understanding social media conversations through to analyzing customer and sales data.
Current data science tools demand learning to code in Python or R (which takes years until someone is fluid enough). They don't guide you either. Don't help you discover what methods and techniques are appropriate for different kinds of analysis (data cleaning, enrichment, modeling) to solve many business problems. These tools aren't very interactive (you need a quick feedback loop to understand what you are doing), and you can only work with structure data (numerical and categorical data). They miss all the possibilities we now have to analyze texts and images thanks to AI's latest advancements.
Go and check our docs to see how the product works.
In our Youtube channel, you will find more detailed videos.
Graphext actually started at the beginning of 2014. The two co-founders, Victoriano and Miguel, spent the first years building another product that inspired them to later, in 2017, raise money from venture capital ( Kfund is our main investor ) to build Graphext. Up to this date, the company has received over 3M euros in funding.
At the same time, we also keep growing our revenue as we sign more and more customers every month.
You will work in our business team. Your mission will be to focus on finding the right people to use and buy Graphext, people working in analytics, business intelligence, and insights from industries like FMCG, pharma, telco, fintech or communication.
We expect you to be able to talk to both: business and technical people (data scientists, business analysts), but don't worry if you don't have a technical background; we'll teach you the language and the concepts you'll need to master to qualify these potential customers. So, if you are excited about data analytics in general, this could be a great opportunity to start a career path with a bright future.
We also expect you to collect relevant information about the people you will talk to, like what tools they are already using to solve the problems we solve, what features you present they find more interesting, or what they wish our product could do. This information is essential for the development of the product.
Leading the business team is Brais who, beyond business and sales, is covering operations duties too. For years, Brais has been diving into data science teams along with different industries (fintech, pharma, hedge funds, telco, banking, retail...), collecting a deep knowledge about data analysts' mindset and the biggest pains all these roles are facing from a technical and operational perspective.
Paul will be the person with who you will spend most of the time. He joined Graphext in December 2020. Since then, he has been connecting Graphext with the data industry, learning about its needs, and creating the sales automation workflow that allows us to reach all those right profiles most efficiently. Paul is a good benchmark about how your Graphext career plan will look. He studied business but beyond that, he has felt a real curiosity for Data Science trends and technologies. He applied for this position and after 12 months, he is now an Account Executive.
Sometimes, you'll also work with Sergio. He is in charge of customer success. He will teach you the success stories from our current customers: what use cases are more mature to sell now and which ones are more experimental.