Our Data Science and Machine Learning practice, is made up of two teams that work collaboratively whilst having their own specific areas of expertise.
We have a track record of building teams from scratch or providing world class expertise to companies that appreciate and harness the power of data by attracting the world's very best talent.
Financial firms have always been pioneers when it comes to working with, analysing and forming predictions utilising large, complex data sets. They continue to push the boundaries of what is possible and attract the brightest minds from research hubs, technology firms and academia.
The growth of the tech sector runs in parallel with the growth of data. Modern tech firms embed a data-driven culture in almost everything they do, from strategy, to reporting to developing new products. Recognising that data is their most powerful asset, data scientists in this space are often highly commercial, utilising cuting edge statistcial techniques to drive bottom line growth.
We partner closely with private equity on two fronts, to help build their internal data science teams as well as building teams within portfolio companies. Data science is a rising trend for private equity industry and Campbell North are proud to sit at the heart of it, helping some of the biggest PE funds with all their advanced analytics needs.
Data is part of everyday life these days, with the collection and analysis of huge quantities of data being an integral part of modern day business, with a multitude of use cases and with billions of dollars of revenue being generated every day.
Our clients tend to be at the cutting edge of data extraction and analysis. Hiring leading lights in their field to tackle high impact projects with innovative solutions.
Gaining actionable insight
Data Science is the set of skills and techniques necessary to draw insights from these vast quantities of data whether it be within healthcare, finance or e-commerce. We work with Data scientists who combine software engineering, statistics, machine learning, data visualization with business understanding (a rare and sought after mix) to extract actionable insights, that have a direct impact on a firm's performance.
Providing analytical horsepower
Working with data scientists to assist with the process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and supporting decision making. There are a variety of specific data analysis methods that are commonly used including data mining, text analytics, business intelligence and data visualization.
Extracting meaningful data
Data Engineering is undoubtedly the most important aspect of a successful data team and without the right data set or correct infrastructure, you cannot perform or begin any analysis or predictions. Split into two categories; analytics engineering and data infrastructure. Analytics engineers acquire and ingest large amounts of unstructured data sets through ETLs and data pipelines. Whereas data infrastructure engineers will be responsible for building the data infrastructure and architecture, that enables quick access and utilisiation of petabytes of data.
Our Machine Learning practice specialises in sourcing the top percentile of global Machine Learning talent from Research Scientists, Applied Scientists, Research Engineers and Engineers.
We partner with a portfolio of industry leading companies, including publicly traded global tech giants, cutting-edge series A-C start-ups,research labs and the world’s most elite quantitatively-driven hedge funds and proprietary trading firms.
If you are a company looking to take your technology and teams to the next level, or a Scientist/Engineer looking to take your career to the next level then please get in touch
Industry leading Researchers dedicated to defining what is state of the art
Research Scientists are responsible for designing and carrying out experiments to advance scientific discovery and keep pushing the boundaries of what is considered state-of-the-art. We work with industry leading Research Scientists at all levels of seniority, from entry-level through to Tech Leads and Managers. All of whom have strong publication records with their work being accepted at leading conferences, such as NeurIPS, ICML, ICLR, ACL, NAACL, EMNLP and CVPR.
Experienced Researchers dedicated to solving real world business problems
Applied Scientists are also responsible for advancing scientific research but are more concerned with applying research to solve specific real-world business problems. Typically, Applied Scientists are strong Researchers, who also have the capability to implement their solutions at scale. We work closely with our business partners to understand the problems they are trying to solve and with Applied Scientists who are motivated by solving these domain-specific problems.
Elite Engineers with extensive experience of building scalable technology
Machine Learning and Research Engineers are primarily responsible for designing, building, optimizing and productionizing models created by Scientists and developing highly scalable algorithms to improve or create new technology. We work with Engineers that have strong domain expertise and Software Engineering capabilities, with demonstrable experience of working with Scientists to scale businesses’ technologies to new hights.