120 Digital Technologies jobs in Stoke on Trent

Data and Analytics (Football)
Greater Manchester
£40,000-£45,000

Excellent opportunity for a Senior Data Analyst, Performance Analyst, or Scout from within professional football to join an ambitious set up offering the chance to get involved in recruitment across all teams as this club looks to shift their recruitment culture.

In this role you will build reports on current players, on current and fu.

WHJS1_UKTJ

• Assist senior analysts in data extraction and manipulation from various sources.
• Perform data cleansing and validation to ensure accuracy and consistency.
• Contribute to the creation of visualizations and reports using tools like Tableau or Power BI.
• Support the analysis of complex datasets to identify business insights and opportunities.
• Participate in team meetings and training sessions to enhance technical skills.
• Learn and apply statistical modeling techniques.
• Maintain data documentation and adhere to data governance policies.

Our OEM Client based in Gaydon, is searching for a Senior Data Analytics Specialist to join their team, Inside IR35. This is a contract position until 31st March 2026.

Umbrella Pay Rate: £33.64 per hour.

Duties:

This role (Data Analytics - Software and Systems Testing) is focused on ensuring the integrity, consistency, and usability of software and systems testing data across all domains created in J.

WHJS1_UKTJ

• Intensive training in data analytics tools and methodologies.
• Hands-on experience with real-world data projects.
• Mentorship from industry experts in data science.
• Exposure to various data analysis techniques, including statistical modeling and machine learning.
• Development of skills in SQL, Python/R, and data visualization tools.
• Opportunity to build a professional portfolio and network.
• Fully remote learning and working environment.
• Structured learning path designed for recent graduates.
• Contribution to impactful business insights.

• Recent graduate with a degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Economics, Engineering).
• Strong analytical and problem-solving abilities.
• A keen interest in data and its applications.
• Basic understanding of programming concepts (Python or R is a plus).
• Familiarity with database concepts (SQL is a plus).
• Excellent communication and collaboration skills.
• Ability to work independently and manage time effectively in a remote setting.
• Proactive learner with a desire to develop new skills.
• Enthusiasm for a career in data analytics.

Data and Analytics (Football)
Greater Manchester
40,000-45,000

Excellent opportunity for a Senior Data Analyst, Performance Analyst, or Scout from within professional football to join an ambitious set up offering the chance to get involved in recruitment across all teams as this club looks to shift their recruitment culture.

In this role you will build reports on current players, on current and future transfer targets, and map several different leagues in the UK and in Europe to try and spot the profile of player that will thrive in different systems. You'll define KPI's and performance metrics for the databases you build using SQL. You'll deliver data-backed insights in senior-level recruitment meetings.

The ideal candidate will be data-savvy and competent working with SQL, R, Python, and Excel. Candidates must have experience with at least one of the following data providers: Wyscout, Opta, Hudl, Skillcorner, StatsBomb, or similar. Candidates will have some proven experience as a Senior Data Analyst, Scouting, or Performance Analytics within professional/elite level football.

This is a fantastic opportunity to help shape the future of recruitment for years to come at an ambitious club!

The Role:
*SQL, R, Python, and Excel
*WyScout, Opta, Hudl, Skillcorner, StatsBomb or similar
*Working with MD, Owner, Manager, and the recruitment team to select targets for recruitment
*Defining KPIs and metrics on which to base decision making

The Person:
*Experience within professional/elite level football
*Senior Data Analysis, Performance Analysis, and/or Scouting experience
*Commutable to the Greater Manchester area
*SQL, Python, R, and Excel experience

Reference Number: BBBH(phone number removed)

To apply for this role or for to be considered for further roles, please click "Apply Now" or contact Tommy Williams at Rise Technical Recruitment.

Rise Technical Recruitment Ltd acts an employment agency for permanent roles and an employment business for temporary roles.

The salary advertised is the bracket available for this position. The actual salary paid will be dependent on your level of experience, qualifications and skill set. We are an equal opportunities employer and welcome applications from all suitable candidates.

• Design, develop, and deploy sophisticated machine learning models for insurance applications such as risk assessment, fraud detection, pricing, and customer segmentation.
• Analyze large, complex datasets from various sources to identify trends, patterns, and actionable insights.
• Collaborate with actuaries, underwriters, claims specialists, and business stakeholders to understand their analytical needs and translate them into data-driven solutions.
• Clean, process, and transform data to ensure its quality and suitability for analysis and modeling.
• Utilize statistical software and programming languages (e.g., Python, R) for data manipulation, analysis, and model building.
• Develop and maintain data visualizations and dashboards to communicate complex findings effectively to both technical and non-technical audiences.
• Stay abreast of the latest advancements in data science, machine learning, and AI, and explore their applicability to the insurance domain.
• Contribute to the development and implementation of data governance best practices.
• Mentor junior data scientists and contribute to the growth of the data science community within the organization.
• Evaluate the performance of deployed models and iterate to improve accuracy and business impact.

• Master's degree or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Minimum of 5 years of professional experience as a Data Scientist, with a proven track record in the insurance industry.
• Strong expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and predictive analytics.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy).
• Experience with SQL and working with relational databases; familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent data visualization skills using tools like Tableau, Power BI, or Matplotlib/Seaborn.
• Strong understanding of insurance products, operations, and common business challenges.
• Exceptional analytical, problem-solving, and communication skills.
• Ability to work independently in a remote setting, manage multiple projects, and meet deadlines.
• Experience with cloud platforms (AWS, Azure, GCP) is desirable.

• Design, develop, and implement sophisticated statistical models and machine learning algorithms to solve complex business problems within the FMCG domain.
• Analyze large, diverse datasets from various sources (e.g., sales, marketing, supply chain, customer feedback) to identify trends, patterns, and opportunities.
• Build predictive models for forecasting sales, demand, customer churn, and marketing campaign effectiveness.
• Develop customer segmentation models and personalization strategies.
• Collaborate with business stakeholders to understand their needs, define analytical requirements, and translate findings into actionable recommendations.
• Perform data wrangling, feature engineering, and data visualization to prepare data for analysis and present results.
• Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence.
• Mentor junior data scientists and contribute to the team's technical growth.
• Communicate complex analytical results and insights clearly and concisely through reports and presentations.
• Ensure the ethical and responsible use of data throughout the analytical process.

• Master's or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Minimum of 5 years of professional experience in data science, with a strong focus on predictive modeling and machine learning.
• Proven experience applying data science techniques within the FMCG industry is highly preferred.
• Proficiency in programming languages such as Python or R, and associated data science libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch).
• Strong SQL skills for data extraction and manipulation.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Deep understanding of statistical modeling, machine learning algorithms (regression, classification, clustering, deep learning), and experimental design.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain technical concepts to a non-technical audience.
• Experience working in a cloud environment (AWS, Azure, GCP) is a plus.

• Design, develop, and implement advanced statistical and machine learning models.
• Work with large, complex datasets to extract actionable insights and build predictive capabilities.
• Perform data mining, data cleaning, and feature engineering.
• Validate and test models for accuracy, performance, and robustness.
• Translate business requirements into technical data science problems.
• Communicate complex analytical findings clearly to both technical and non-technical audiences.
• Collaborate with engineers and product managers to deploy models into production.
• Mentor and guide junior data scientists, fostering a culture of learning and innovation.
• Stay current with the latest advancements in data science, AI, and machine learning.
• Contribute to the development of data science best practices and standards.

• Advanced degree (MSc or PhD) in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline.
• Minimum of 5 years of experience in data science, with a focus on predictive modeling and machine learning.
• Proficiency in programming languages such as Python or R, and associated data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas).
• Experience with SQL and database technologies.
• Strong understanding of statistical modeling, machine learning algorithms, and experimental design.
• Experience with big data technologies (e.g., Spark) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain technical concepts to diverse audiences.
• Proven ability to work independently and manage multiple projects simultaneously in a remote setting.
• Experience with cloud platforms (AWS, Azure, GCP) is desirable.