Qarik

What We Do

Data Science

We use our wide experience of data exploitation to help our partners to build new products, become more efficient and do more with the resources they already have.

Our team has worked on everything from researching the fundamental secrets of the universe with NASA to delivering production models that serve millions of customers. Together we can gain insights from data using the full range of tools available today, from Natural Language Processing, through deep learning to the growing fields of MLOps and explainable AI.

Beyond this we think one of our most valuable skills is an ability to audit the existing business processes of a company and use our experience to suggest new ways to gather and exploit data that can build value. This might mean digitising and combining existing data that is lost in the cracks of the existing business, automating costly manual processes or creating new products to complement existing offerings.

Value is the lodestar in all our work. We will always work with our partners to create the simplest possible interventions to reach their goals and we are experts at designing market analysis to let you know when it makes sense to buy and when to build. We think this is an important discipline in a field where chasing the buzz of the latest ML trend often leads people astray.

Why it matters

There are 4 key ways our data science skills can deliver value for your business:

  • Alongside our data engineers we can unlock your currently stranded data & put it to work for you
  • Identify gaps in your available data and, where possible, identify open source or proprietary data that will close that gap and help you do more
  • Interrogate your business model and identify opportunities to:
    • Improve the efficiency of your current operations
    • Enhance your existing products and sales channels
    • Exploit existing and new data to build new product lines
  • Draw on our wide experience to select appropriate technologies, from statistical inference to machine learning, to deliver new business value

How we can deliver value

In the two example projects below, we focus on using our skills and experience corralling and exploiting data to deliver measurable value for our partners:

Example 1

Our partner has valuable information stored in pdf format (or even printed documents) that makes it difficult to draw connections between documents, analyse and exploit the information at scale. We can build a machine learning-powered pipeline to scan the documents, segment the content, identify important topics or entities mentioned and store the results in a highly structured, machine-readable data lake. Now the data in those documents can power business intelligence tools, feed into other ML models or form the basis of new products and services.

Example 2

Our partner already uses a variety of data sources to make certain business decisions but the evaluation of the data is ad-hoc and varies over time. Perhaps they prioritise potential customer acquisition by combining data from their CRM, geolocation and other properties of existing customers, third party customer intelligence services and the industry knowledge of their own sales team. Each of these is valuable but they will not be used to their fullest extent if each sales team lead is using and combining the data in their own unscientific way. We can work with the sales team to build a coherent, comprehensive machine learning model to predict the most likely new customers based on the success and failure of previous approaches. Now the whole team can benefit from the combined best-practices from across the company, implemented in an objective and transparent way.

Data Science in Action

International Business Data & Insights Organization

View Case Study