Data Services

Data Science & AI Services

Overview

Data is the driving force behind innovation and growth for businesses across the public and private sectors. For a business to adapt and grow, it must have approach to data science that's accessible and applicable to the unique challenges of every organisation.

Methods Analytics offers a broad data science service that can significantly expand your data capabilities. We offer transparent, explainable machine learning and artificial intelligence that delivers predictive models that your users can understand and trust. We follow ethical and coding best practices to design solutions and validate our results routinely, ensuring results that are reproducible and reliable. By helping you find relationships and patterns hidden in your data, we’ll unveil insights and future-proof your investment by progressively monitoring our solutions.

Fundamentally, we believe that data science is not just about algorithms and models; it's about transforming data into actionable insights that empower organisations to make informed decisions. We'll work closely with you to understand your context, your use cases and your constraints, helping us to deliver solutions that are specifically tailored to your particular needs.

Working with Methods Analytics as your partner, you will be empowered to unlock the full power of AI and data science in your current working practices, helping you to increase productivity, drive efficiency and create a data-driven future for your organisation.

To learn more about our AI and data science consultancy services, get in touch with us today.

What we deliver

Our AI and data science offering

We deploy data science and AI services that are not only impactful today, but also allow you to build capabilities that you can continue to develop tomorrow. Our offerings are tailored to meet the needs of our clients across multiple sectors, ensuring that data science becomes an integral part of your organisation's growth and success.

Here are the data science consulting services we deliver:

Developing data science solutions

We are more than just a service provider; we are a trusted data science partner specialising in developing solutions across the public and private sectors. Our expertise spans:

Predictive analytics, forecasting and risk modelling: leveraging advanced algorithms to predict future trends, assess risks and create a proactive data strategy, based on structured and unstructured data analysis.
Machine learning, deep learning and reinforcement learning: utilising cutting-edge techniques to create intelligent systems that learn and adapt over time.
Natural language processing (NLP): applying NLP for topic modelling, document labelling and classification, named entity recognition and linking, knowledge graphs, ontologies, and sentiment analysis.
Statistical analysis and task automation: employing statistical methods to uncover insights and automate repetitive tasks, enhancing efficiency and accuracy.
Generative AI and large language models (LLMs): harnessing the power of generative AI models to identify patterns and structures within data sets, and provide new efficiencies in the use of information.

No matter what your requirements may be, you can rely on us to use the best tool available for your goal - whether this means utilising cutting-edge innovations, or well-established tried-and-true solutions.

Data science proof of concept

Data science is about experimentation and evidence, and we're here to help you validate your ideas. Whether you have a concept to develop or have been inspired by an existing data science use case elsewhere, we'll assist you in assessing its feasibility, legality and ethics. Our approach to developing proofs of concept allows you to rapidly create a minimum viable product and test it with users, all at minimal cost. Together, we can provide the evidence that your concept is worth building into reality.

Data science as a service

Building and nurturing an effective data science team can be challenging. We offer data science as a service to help you skip over these challenges, embedding talented teams of experienced data scientists into your organisation. Our deep sector experience means our teams will hit the ground running on day one, allowing you to immediately begin delivering at scale and building the future at pace.

We're also able to support your in-house team-building efforts through our data science service, from defining functions and roles to interviewing and onboarding new recruits.

Use case evaluation

The applications of enterprise data science are vast, but identifying those that deliver real value is crucial. We'll evaluate your use cases, assessing feasibility, impact and development requirements based on your existing data and setup. By combining qualitative research with quantitative assessment, we provide an evaluation that makes a compelling case for development.

Our commitment to delivering impactful and sustainable data science solutions is unwavering. We understand that every organisation is unique, and we tailor our services to meet your specific needs and challenges. Together, we'll explore the endless possibilities of data science, turning ideas into reality and driving meaningful change.

What is the application of data science in modern enterprise?

In today's rapidly evolving digital landscape, the role of data science extends far beyond mere data collection and knowledge management. Here's a closer look at the modern applications of data science:

Informed decision-making: data science equips organisations with actionable business insights derived from complex data. By analysing patterns and trends, decision-makers can make more informed, evidence-based decisions that align with organisational goals and market dynamics.
Enhancing productivity and efficiency: through routine process automation and optimisation techniques, data science streamlines your operations, reduces manual efforts and minimises errors. It enables organisations to allocate resources more effectively, enhancing productivity and operational efficiency.
Personalisation and customer engagement: data science plays a vital role in understanding customer behaviour and preferences. It allows businesses to create personalised experiences, targeted marketing campaigns and tailored products or services, leading to increased customer engagement and loyalty.
Risk management and fraud detection: in sectors like finance and healthcare, data science is instrumental in identifying potential risks and fraudulent activities. Predictive models and anomaly detection algorithms help in early identification, allowing for proactive measures to mitigate risks.
Innovation and new product development: data science fosters innovation by uncovering hidden opportunities and unmet needs. It aids in the development of new products, services and business models that cater to evolving market demands.
Supply chain optimisation: the process automation capabilities of a strong data science strategy can help to optimise supply chain operations. From demand forecasting to inventory management, it ensures that the right products are in the right place at the right time.
Human resource management: data science delivers data-driven insights that help shape how organisations manage their human capital, from talent acquisition and performance analysis to employee retention.
Social impact and sustainability: in an era when driving positive social impact and sustainable practices is more vital than ever, data science insights can be leveraged to address challenges ranging from healthcare accessibility to climate change mitigation.

In these ways, data science provides organisations with a strategic edge in a highly competitive market. As a strategic partner, we specialise in harnessing the power of data science to help organisations navigate the complexities of the modern business landscape, turning data into a strategic asset that fuels growth and success.

What are the applications of AI in modern data science?

AI has become an integral part of modern data science, revolutionising the way data is analysed, interpreted and utilised. The synergy between AI and data science has led to groundbreaking advancements across various domains, delivering significant benefits within the following applications:

Data preprocessing and cleaning: AI algorithms can automatically detect and correct errors in datasets, fill in missing values, and even identify and remove outliers. This not only speeds up the process, but also improves the quality of the data, which is vital for obtaining accurate insights.
Predictive analytics: AI algorithms, particularly machine learning models, are able to make data-driven predictions based on historical data. This includes forecasting sales, predicting customer churn, or identifying potential market trends, all of which can provide more accurate and timely insights than traditional statistical methods.
NLP analysis: from sentiment analysis and chatbot development to advanced text mining and summarisation, NLP algorithms can process and analyse large volumes of unstructured text data, turning it into actionable insights.
Image and video analysis: AI algorithms can be used to analyse visual data, automatically tagging images, detecting anomalies, or identifying objects in real-time video feeds.
Real-time analytics: AI can process and analyse data in real time, providing businesses with immediate insights to inform their decision-making. This is particularly useful in sectors where instant insights could be the difference between success and failure.
Automation of complex tasks: AI can automate complex data science tasks such as feature selection, hyperparameter tuning, and even selecting the right machine learning model for a given task. This not only speeds up the data science workflow, but also makes it more accessible to non-experts.

The applications of AI in modern data science are vast and continually evolving. From enhancing business operations to driving social change, AI's integration with data science is shaping the future in profound ways - which is why we are dedicated to helping you unlock these benefits.

We leverage the latest AI technologies to deliver innovative data science solutions that align with your unique challenges and objectives. Our expertise in AI and data science positions us at the forefront of this exciting frontier, empowering your organisation to harness the full potential of data-driven intelligence.

What are the advantages of data science as a service?

Data science as a service (DSaaS) is an innovative approach that allows organisations to leverage data science capabilities without the need to build and maintain an in-house team. By outsourcing these tasks to specialised data science consulting firms, you can tap into expert knowledge and advanced tools.

The benefits of doing so are potentially significant:

Easy access to expertise - DSaaS provides access to a team of data science experts with diverse skills and experience. Whether it's machine learning, statistical analysis or predictive modelling, you can access specialised knowledge without the need to hire full-time staff.
Cost-effectiveness - building an in-house data science team can be expensive when factoring in salaries, training and infrastructure costs. DSaaS offers a more budget-friendly solution, allowing you to pay for the services you need when you need them.
Scalability and flexibility - DSaaS offers scalability and flexibility to suit your organisation's changing needs. Whether you need to ramp up for a specific project or scale down during slow periods, DSaaS can adapt to your requirements.
Rapid deployment and innovation - with DSaaS, you can quickly launch data science projects without the delays associated with recruiting, training and setting up infrastructure. This accelerates innovation and helps you stay ahead of the competition.
State-of-the-art tools and technologies - DSaaS providers invest in the latest tools and technologies, ensuring that you benefit from cutting-edge solutions. From AI-powered algorithms to advanced data visualisation tools, you gain access to the best in the industry.
Compliance and security - professional DSaaS providers adhere to industry standards and regulations, ensuring that your data is handled with the utmost security and compliance. This is particularly vital in sectors with stringent data protection laws.
Focus on core business functions - by outsourcing data science tasks, your team can focus on core business functions and strategic initiatives. This allows for better allocation of resources and enhances overall productivity.
Continuous monitoring and optimisation - DSaaS includes ongoing monitoring and optimisation of data science models and algorithms. This ensures that the solutions remain effective and evolve with changing trends and business needs.
A collaborative approach - by working closely with your AI and data science services provider, you can ensure that these solutions are fully integrated with your organisation's strategy and culture.

This is why data science as a service offers a compelling alternative to traditional in-house data science teams, allowing even small and medium-sized organisations to access top-tier data science capabilities that were previously only available to large corporations with significant budgets.

We offer best-in-class DSaaS solutions, ensuring that your organisation benefits from the best that data science has to offer, without the complexities of managing it in-house. By working with us, you'll be able to unlock valuable insights from your data sources and translate these into actionable business intelligence.

The benefits of AI and data science

Data science and AI are transformative technologies that can reshape the way your organisation operates, makes decisions and engages with stakeholders in various ways:

Enhanced decision-making - decision-making processes driven by data science and advanced analytics lead to more informed and strategic choices. The impact can be measured in terms of improved efficiency, reduced risks and increased profitability.
Cost savings - through process automation and optimisation, AI and data science can streamline various business activities, reducing the need for manual intervention. This leads to significant cost savings, as organisations can allocate resources more effectively. The reduction in operational costs can be quantified and tracked over time.
Increased revenue - AI-powered predictive analytics can help organisations identify new revenue streams and opportunities for growth. By understanding customer behaviour and market trends, businesses can create targeted campaigns and personalised experiences, leading to increased sales and customer retention, as well as improved client satisfaction.
Risk mitigation - artificial intelligence and machine learning algorithms can be used to detect a variety of threats, including compliance issues, quality control problems, cyber security risks and changes in market dynamics. This allows organisations to take proactive measures to mitigate risks.
Innovation and agility - data science and AI foster a culture of innovation by enabling organisations to experiment, iterate and adapt quickly. They support the development of new products, services and business models, enhancing the organisation's competitive edge. Metrics such as time-to-market and innovation ROI can be used to measure success.
Sustainability and social responsibility - data science and AI can also contribute to sustainability goals by optimising resource utilisation, reducing waste and supporting environmental monitoring. The positive impact on sustainability metrics, such as carbon footprint reduction and energy efficiency, can be tracked and reported.

The measurable benefits of data science and AI services extend beyond mere numbers; they reflect a profound transformation in the way your organisation operates and creates value. We'll work closely with your team to ensure that all of these benefits can be realised, allowing you to unlock new potentials, drive growth, and build a resilient and responsible future.

Our approach

Our approach to data science is a comprehensive and tailored process that ensures alignment with your organisation's unique needs and objectives. Our approach is built around four key stages: Discover, Design, Develop and Deploy.

Discover

Data science provides your organisation with an ever-expanding set of innovative solutions to real-world problems. Our user researchers are here to help you uncover the opportunities where we can have the most valuable impact.

We’ll use interviews and workshops to understand business requirements, gather user needs and define an engaging problem statement that is backed up by a firm business case. We’ll explore any attempts that have already been made to address the problem, source the data available to support the requirements, and then validate all of our findings with stakeholders.

Design

Our data scientists will use research findings to explore a range of possible solutions, approaches and methodologies. We’ll propose a design that can be developed from proof-of-concept to minimum viable product and through to a fully productionised model. We advocate for explainable and interpretable models, selecting the most appropriate tool for the job in all instances. We’ll explain our work throughout, providing technical and non-technical documentation in a format that works best for your team.

Our design process rigorously controls for any bias against groups or individuals, providing complete transparency around our selection of model characteristics, and ensuring we represent the populations you serve.

Develop

Our integrated engineering teams ensure we can develop those innovative designs at the scale you need to suit your use case, timeline and budget. Once we've developed the maths, we can build interactive dashboards to allow you to explore your data, drill down and filter your insights.

We develop your solution through continuous integration, following coding best practices, versioning and unit testing to build future-proof solutions. By reducing the need for your users to undertake repetitive, time-consuming and error-prone tasks, we give them time to focus on using the outputs to make better-informed decisions.

Deploy

We don't just experiment - our team has all the capabilities needed to deploy your new data science solution into production, and into the hands of decision-makers. Whether it's embedded into your existing systems and processes, developed on a bespoke platform, or integrated with a third party, we'll ensure the user experience is as seamless as possible.

Our intuitive solutions, accessible documentation and hands-on training sessions will allow your team to confidently use the analysis and put it into the hands of decision-makers across your organisation.

Our preferred tools

In the rapidly evolving field of data science, the right tools are essential for delivering effective and efficient solutions. Our data science and AI services are built on a foundation of best-in-class tools that enable us to provide top-tier performance and capabilities.

Python is more than just a programming language; it's a vital tool for data science applications. As an open-source, flexible and beginner-friendly language, Python allows our team to work quickly and integrate systems more effectively. Our specialists are adept at leveraging Python's extensive libraries and frameworks to create tailored data science solutions for your organisation.

Azure Machine Learning is a powerful platform that empowers data scientists and developers to build, deploy and manage high-quality models faster and with confidence. It offers a secure and trusted environment designed for responsible machine learning. With Azure Machine Learning, we can innovate and create solutions that are both scalable and aligned with your organisation's needs.

Amazon SageMaker is a robust tool that helps data scientists and developers prepare, build, train and deploy high-quality machine learning models quickly. It brings together a broad set of capabilities purpose-built for machine learning, allowing us to create solutions that are not only innovative but also responsive to your specific challenges. With SageMaker, we can harness the power of machine learning to deliver insights that drive real value.

Apache Spark™ is a multi-language engine known for its ability to execute data engineering, data science and machine learning tasks on single-node machines or clusters. Its versatility and performance make it an essential tool in our toolkit. Whether we're processing large datasets or implementing complex algorithms, Apache Spark™ enables us to do so with speed and precision.

Tools of specialty

Python

Python is an open source, flexible and beginner-friendly programming language that lets you work quickly and integrate systems more effectively. Our team are specialists at using Python for data science applications in the public sector.

Azure Machine Learning

Azure Machine Learning empower data scientists and developers to build, deploy and manage high-quality models faster and with confidence. Innovate on a secure, trusted platform designed for responsible machine learning (ML).

Amazon SageMaker

Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning models quickly by bringing together a broad set of capabilities purpose-built for machine learning.

Apache Spark™

Apache Spark™ is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.

Get in touch

Ready to transform your organisation with our data science and AI services? Contact us today to learn more about how we can help you maximise the potential of your data.

Case Studies

Becoming a Data Driven Organisation

The development and use of digital technologies in recent years has led to a growth in the volumes of data that is being collected, stored, and shared within organisations. Data now influences every part of our lives from recommendations to new TV shows or which adverts or friends we see content from first on social media.

MIBI Engineering - The Driver and Vehicle Licensing Agency (DVLA)

They look after more than 49 million driver records and more than 40 million vehicle records. They collect around £7bn a year in vehicle excise duty (VED). Their goal is to get the right drivers and vehicles on the road, as simply and safely as possible.