Data > Data Science Page_HERO

Data Science.

Understand what happened then, what’s happening now & what happens next if…

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Grid Four Columns - DataScience

How we help.

We help you define, prototype, develop, deploy and manage advanced analytic models that can be trained to continually improve accuracy, relevance and quality. Here’s some of the typical customer challenges and opportunities we see.

DataScience - Element - KeyMetrics

We need to get more scientific about forecasting our key business metrics.

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DataScience - Element - Customers

We want to understand our customer profiles better so we can have more targeted conversations.

Brand

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DataScience - Element - Pricing

We need to optimise our pricing strategy to maximise revenue (and/ or other KPIs).

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DataScience - Element - Manual

Our paperwork processing is too time-consuming, manual and repetitive. We need to automate.

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DataScience - Element - Migration

We’re moving to open source (e.g. from SAS to R/Python) – but we lack in-house skill and experience.

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DataScience - Element - Profile

We need to raise the profile of data science in our business with roadmaps, internal stakeholder engagement & technical guidance.

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DataScience - Element - Resources

We need data science resources to help deliver projects due to lack of skills and/or capacity.

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DataScience - Element - Production

We have previously developed models but they need to be productionised to improve and generate value over time.

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Diagram_Our resources and capability - DataScience

Our resources and capability.

The scale and skills of our talented teams (and where to find them).

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Tabs - DataScience - Services 2.0

DataScience 1 - Tab - ML

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DataScience 2 - Tab - Advanced Stats

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Data Science 3 - Tab - Analytic Development

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Data Science 4 - Tab - Learning & Development

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DataScience - Machine Learning

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DataScience - Machine Learning

Machine learning.

As a building block of AI and a core discipline of data science, we develop and deploy right-fit machine learning models that reflect your data maturity. To ensure these models stay relevant and deliver ongoing value, we apply MLOps best practices to optimise scale, supportability and stability.

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DataScience - Advanced Stats

DataScience - Advanced Stats

Advanced statistics.

In the commercial world, Data Science is all about applying relevant mathematical, statistical and computational techniques to create maximum business value and impact.

Our experienced data scientists apply frequentist and Bayesian statistical techniques to tackle business challenges, such as improving estimate accuracy, A/B testing frameworks and numerical optimisation.

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Value Proposition

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DataScience - Analytic Development

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DataScience - Analytic Development

Analytic development.

We develop analytic software including packaged code in R and Python for data scientists, data processing backed web app based on Shiny, Dash and other similar frameworks, open source transformation and related code conversion.

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Value Proposition Inverted

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DataScience - Learning & Development

DataScience - Learning & Development

Learning & development.

According to a DataIQ survey in June 2021, maturing your data science function can deliver an uplift of ~14% of your revenues.

Our senior resources provide technical, strategic and operational guidance to your in-house teams, from classroom training to consulting/ mentoring and tactical/ longer term team augmentation.

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Value Proposition

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What it means to you table - DataScience

How we work and what it means to you.

How it work & what it means to you.

How we work.What it means to you.
Led by business objectives and motivated by delivering real business impact: value and outcome-driven.Accelerate change and drive momentum in the re-investment cycle by delivering early value.
IDEaL Framework: Investigate, Develop, Evaluate and Launch are the steps in a full delivery cycle.Investigate phase de-risks development process. Clearly articulated success criteria, business alignment and minimised risks of project failure.
MLOps: the application of CI/CD and other best practices (e.g. data drift monitoring) to automate ML tasks in experimentation and production.Continuous improvement in model performance and longer term value delivery.
Hive knowledge: we promote a learning and development culture as a team of curious minds, sharing knowledge and latest developments to ensure high delivery quality.Benefit from the latest practices and proven techniques we accumulate over time and across industries.

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IN ACTION

DATA - DataScience CaseStudy

Heathrow Airport

Forecasting airport baggage flows.

As Europe’s busiest airport, Heathrow safely carries hundreds of thousands of passengers through its terminals and onto their flights every day. Its busiest terminal, T5, carries over 30 million passengers each year, so even small advancements in planning and passenger efficiency can have enormous impact on total capacity for the airport as a whole.

We helped Heathrow to build a predictive modelling forecast for future baggage handling requirements based on historical patterns and future flight schedules, including the impact of unplanned events and variants such as weather and air traffic control issues system problems.

Logo - Data - Case Study - DataScience Heathrow

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Career Progression Services

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Explore our other data services -DataScience

Explore our other services.

DATA - OTHER SERVICES - Data Engineering

Data Engineering

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DATA - OTHER SERVICES - BI

Business Intelligence

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DATA - OTHER SERVICES - Data Strategy

Data Strategy

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Lets get started section - Services DataScience

Let’s get started.

We help you create game-changing insight, deliver pivotal data projects and build strong internal analytics capability.

Got a challenge in mind? We’re ready when you are.

Get In Touch

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