Data science and engineering

Big data analytics have become the reality need of many startups. In that context, data scientists write models, and data engineers ensure that the models can run on clean data, in a secured and automated way. We can provide your startup with both profiles.

Our data engineers have experience with heavy extraction, transformation and algorithm automation. Some of our past experience include:

  • data scraping automation to extract millions of comments and reviews for a traveltech startup to generate sentiment analysis across several websites

  • extraction, transformation and storage of over a billion electronic invoices for a fintech startup producing credit analysis for banks

  • multiple redundancy robots for an opentelco startup to extract information in seconds and process a credit analysis based on payment behavior

  • a payment solution for a fintech startup allowing to determine what bill to pay with what payment method

We can also provide you with high quality data scientists proficient in Pythin and R to write the models that will support you big data product. Some of our past experiences include:

  • a complete credit rating on top of electronic invoices to generate a business and credit profiles to support processes at multiple large banks

  • Support Vector Machine based algorithms to allow for automated e-discovery, that is the classification of billions of emails for an legaltech startup

  • collection and processing of website interactions to provide users of an edutech startup with contextualized help

  • Blockchain based analytics of API logs to detect undesirable patterns 

Our data scientists team is experienced with startup work, which means that they are trained to focus less on academic work and more on immediate, bankable results. Our Analyze-to-deliver proprietary methodology is designed to standardize big data projects, and can be used upon request as part of our service.