Data Scientist

Description

The team is growing, and this role designs, builds and delivers data science solutions for clients that tackle complex business problems and produce measurable results.

The work combines programming, data engineering, statistical modelling, machine learning and generative AI to turn data into insights and solutions that can scale.

You will work with clients and internal stakeholders to spot opportunities, build lasting working relationships, and create analytical products and prototypes that support data-driven decisions and business growth.

The company is a global data and technology business operating across financial services, healthcare, automotive, agribusiness, insurance and other sectors. It is listed on the London Stock Exchange, is a FTSE 100 Index company, has about 22,500 employees in 32 countries, and is headquartered in Dublin, Ireland.

Responsibilities

• Assess and bring in new data assets.
• Build prototypes for new products.
• Support sales and offer consultancy.
• Analyse and document large datasets.
• Use machine learning, data mining and text mining to extract value from data.
• Test models and measure how well they score.
• Document and present modelling methods and results.
• Design analytical and AI solutions for internal and external clients, scaled to fit complex business problems.
• Make independent decisions to find new approaches and handle uncertainty in complex situations.
• Set best practices for using company and client data to produce insights.
• Set out business assumptions for relevant solutions.
• Prepare material for knowledge sharing and roundtable discussions.
• Lead programmes that improve client analytical solutions, data quality, model performance and project timelines.
• Guide the team in finding solutions and share your expertise to strengthen the department's contribution.
• Mentor colleagues within project teams.
• Promote analytics through publications and presentations.

Requirements

• Strong Python skills.
• Understanding of data structures and how they apply to marketing, risk and customer management.
• Working knowledge of regression models, XGBoost, neural networks, SVM and ensemble methods.
• 3+ years defining scope and delivering customised analytics projects.
• Deep expertise in advanced algorithms applied to practical business problems.

Conditions

Hybrid role combining remote and in-office work.

Flexible working hours and home office options are available.

Equal opportunity employer: all candidates are welcome, and reasonable adjustments are available on request.

Benefits

• A career path supported by learning and development programmes and unlimited access to online courses, learning materials and books.
• A friendly, collaborative environment with team spirit and recreation time.
• Social benefits including food vouchers, health insurance, a monthly flex allowance, internet coverage, a Sharesave plan, an employee assistance programme and more.