Data Science Consulting

Leverage the experience of some of the worlds finest data scientists to revolutionize your business.

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Benefits of Data Science

Learn why data science provides such incredible value.

Revolutionize Your Organization with Data Science

Data science helps your organization optimize its processes, decision making, and strategy. It is a high level concept that follows basic scientific principals to answer questions from data.

Machine learning, reinforcement learning and analytics are tools used by data scientists to help automate a process, decision, or strategy, but often data science is a first step to validate that the solution is sane.

A data scientist can also help unlock meaningful insights that are hidden within your data. If you’ve got a large amount of data lying around and you don’t know what to do with it, give us a call. We can help you brainstorm potential uses.

Automate Decisions

Automate Decisions

All businesses have to make decisions. Businesses are in fact information machines. Those that can consume, understand and act upon the best information in an optimal way have an inherent advantage over their competitors.

One of the simplest and most effective data science projects that businesses can undertake is to automate parts of the business that consume and act upon big data.

The benefit of a data science solution is that we can improve the consistency and the accuracy of these decisions with advanced analytics, whilst at the same time saving a considerable amount of time.

And by moving these predictive models into a production environment we can remove the manual effort that was previously required to make the decision.

Simplify Processes

Simplify Processes

Processes go hand in hand with business. On the one hand, processes are necessary to standardise practises. But quickly processes begin to eat away at a business' agility and significant sums are spent on employing people to act out these processes.

There is another way. Data science can be used to encoded this processes in a model that can be repeated over and over again all without human intervention.

The time savings can be huge. But more importantly this allows your business to pick and choose when and how these data-oriented solutions are applied. This means that you can still be agile, applying bespoke processes as and when they are warranted. But still maintain the stability of a process driven business.

Competitive Differentiators

Competitive Differentiators

Truly innovative companies are able to build data-driven products that provide a competitive advantage so incredible that all competition becomes obsolete.

Interestingly, these products might not be user visible. For example, manufacturers can automate quality assurance to maximize production speed. And the result of this isn’t directly visible to the end user. But the speed at which manufacturing can take place causes competitors to struggle to reduce costs and remain lean.

Many of these types of products are so called “expert systems”. These systems try to do one thing very well, which is well suited to data science and cloud native software. This also means that these types of products are very domain specific. But lessons from other industries can be utilized anywhere.

The World's Best AI Companies

From startups to the world’s largest enterprises, companies trust Winder.AI.

Data Science Consulting Services

Our services help you extract maximal value from your data

Data Science Consulting Company

Data science is often touted as being an art, but in reality it’s experience that counts.

By choosing Winder.AI as your trusted data science partner, you can be sure that you are leveraging one of the most highly experienced agencies in the world. Our vast experience helps businesses like yous discover value from their data.

Our data science consultants deliver incredible value by evaluating and recommending strategic business decisions to further your organizational ambitions.

Data Analysis

Data Analysis

In the early phases of nearly every project, a thorough data analysis helps you:

  • Understand the data, the domain, in order to make downstream ML or RL more robust
  • Track when, where, how, and why data was created
  • Provide some initial confidence that a problem is solvable
Data Analytics

Data Analytics

When you have a lot of data, but you don’t know what to do with it, data exploration helps you:

  • Ascertain whether data is useful or valuable
  • Catalog data, what it means, and why it might be useful
  • Provide insights that might surprise you
Process Optimization

Process Optimization

You can use your data to help you optimize your current processes:

  • Analyse your data to find the biggest pain points
  • Identify root causes of process inefficiencies
  • Use your data to direct future automation
Supporting Services

Supporting Services

Don’t forget that we have a wide range of other complementary ai technology services that accompany our data science service.

After a data science consulting project, you might consider moving into a machine learning development project that uses deep learning for predictive analytics or data mining for valuable insights.

Then you’ll need our MLOps expertise to maintain accurate predictions and ongoing machine learning governance.

About Us

Winder.AI is a data science consulting firm, and is based in the UK, although we operate globally.

Our data science consulting team delivers incredible value by evaluating and recommending strategic business decisions to further your organizational ambitions.

Collaborative data science team

Our Approach to Data Science Consulting

Successful consulting arises from decades of experience. Take a look at our tips for a successful data science consulting project.

Data Science Consulting Process

1. Business Context

Any problem demands context from the business. A solution for one industry may not be applicable to another, nor is every business the same. Establishing shared context helps get the project off to the right start.

2. Stakeholder Inclusion

More than just identification, we find projects are optimal when key stakeholders are including in the project. With “skin in the game”, stakeholders are far more likely to collaborate to produce a better overall solution.

3. Problem Definition

A key phase where business problems are defined and prioritized. It is worth spending time to get this right, as subsequent effort could be ineffective and wasted.

4. Domain Knowledge Transfer

Businesses are often experts in their own domain. This domain expertise is valuable to help direct future solutions.

5. Data Analysis

Any data science consulting involves a limited amount of actual data science. In this phase expert data analysts extract knowledge from the data. This often leverages actionable insight.

6. Research and Validation

Following analysis, some time is often spent validating results or confirming value.

7. Ethical/Legal/Safety Analysis

Any work that arises from the consulting should be de-risked in terms of ethical concerns, legal ramifications, or safety risks. This step depends on the industry, the domain, and the context of the problem.

8. Strategic Solution

A solution is presented back to key stakeholders. In many projects we then move into an implementation phase. Other times we step back and perform another iteration to find a better problem and improve your data strategy.

Optimizing for Value Generation

Businesses have three core operational functions. Processes define how businesses run. Decisions decide when businesses are run. Strategies define why businesses are run.

Software has successfully automated many business processes. Data science automates decisions and strategies via machine learning and reinforcement learning, respectively.

By leveraging our data science consulting services we can help you automate the top two most valuable tiers in the pyramid, to make your organization more efficient and profitable.

The value of reinforcement learning, courtesy of our Reinforcement Learning book.
The OODA loop for continuous innovation.
Winder.AI’s data science consulting strives for continuous innovation. Courtesy of our Reinforcement Learning book.

Continuous Innovation

The infamous OODA loop, originally developed by the US military, is of particular use during our work because it helps promote innovation.

At every phase we look for opportunities to add value and make your products and services better. Our clients find that our work greatly exceeds their expectations due to the extra value presented by our solutions.

Selected Case Studies

Some of our most recent work. You can find more in our portfolio.

Using Reinforcement Learning to Attack Web Application Firewalls

Introduction Ideally, the best way to improve the security of any system is to detect all vulnerabilities and patch them. Unfortunately this is rarely possible due to the extreme complexity of modern systems. One primary threat are payloads arriving from the public internet, with the attacker using them to discover and exploit vulnerabilities. For this reason, web application firewalls (WAF) are introduced to detect suspicious behaviour. These are often rules based and when they detect nefarious activities they significantly reduce the overall damage.

Helping Modzy Build an ML Platform

Winder.AI collaborated with the Modzy development team and MLOps Consulting to deliver a variety of solutions that make up the Modzy product, a ModelOps and MLOps platform. A summary of this work includes: Developing the Open Model Interface Open-sourcing chassis, the missing link that allows data scientists to build robust ML containers Model monitoring and observability product features MLOps and model management product features The Problem: How to Build An ML Platform Modzy’s goal is to help large organizations orchestrate and manage their machine learning (ML) models.

How To Build a Robust ML Workflow With Pachyderm and Seldon

This article outlines the technical design behind the Pachyderm-Seldon Deploy integration available on GitHub and is intended to highlight the salient features of the demo. For an in depth overview watch the accompanying video on YouTube. Introduction Pachyderm and Seldon run on top of Kubernetes, a scalable orchestration system; here I explain their installation process, then I use an example use case to illustrate how to operate a release, rollback, fix, re-release cycle in a live ML deployment.

Recent Data Science Articles

Find more articles in our blog.

5 Productivity Tips for Data Scientists

Many articles talk about how professionals can make their workdays extra productive. However, for people like data scientists, whose jobs are extremely demanding, some tips are more valuable than others. For instance, it is important that you analyse how you spend your time. In the same breath, it would be in your best interest to organise your time into blocks, as these can help you focus on tasks – one at a time and without any interruption – and automate any process that you repeat.

Improving Data Science Strategy at Neste

Winder.AI helped Neste develop their data science strategy to nudge their data scientists to produce more secure, more robust, production ready products. The results of this work were: A unified company-wide data science strategy Simplified product development - “just follow the process” More robust, more secure products Decreased to-market time Our Client Neste is an energy company that focuses on renewables. The efficiency and optimization savings that machine learning, artificial intelligence and data science can provide play a key role in their strategy.

How We Work With Cloud-Native Data Science: An Interview With Phil Winder

Start Your Data Science Consulting Project Now

The team at Winder.AI are ready to collaborate with you on your data science consulting project. We will design and execute a solution specific to your needs, so you can focus on your own goals. Fill out the form below to get started, or contact us in another way.