Data Scientist (Remote)

Experian

2d • Remote

About The Position

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. We are seeking a Data Scientist to join our Data Enrichment team focused on improving data quality, operational efficiency, and business decision-making within a large-scale commercial data repository. This role blends hands-on modeling, technical leadership, and cross-functional collaboration to drive measurable improvements in data assets and business processes. Reporting to the Manager of Data Analytics, you will play a key leadership role in designing, developing, and deploying machine learning and GenAI-driven solutions that enhance data quality, automation, and insight generation across commercial financial services data domains.

Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a related quantitative field (Master's degree preferred).
• 5+ years of professional experience in data science, machine learning, GenAI, or advanced analytics roles.
• Proven experience leading end-to-end machine learning initiatives from problem definition through deployment in production environments.
• Strong foundation in statistics, experimental design, and causal inference.
• Proven experience leading end-to-end machine learning initiatives from problem definition through deployment in production environments.
• Strong foundation in statistics, experimental design, and causal inference.
• Advanced proficiency in: Python (pandas, NumPy) Distributed processing frameworks (e.g., Spark / PySpark) SQL (advanced query design and optimization)
• Experience with ML frameworks such as scikit-learn, TensorFlow or PyTorch.
• Experience designing and implementing solutions leveraging large language models (LLMs), such as OpenAI and/or Google Gemini.
• Experience deploying, monitoring, and maintaining models in production environments.
• Familiarity with version control (Git, Bitbucket) and collaborative development workflows.
• Experience working in Agile/Scrum environments.

Responsibilities

• Design and deploy scalable machine learning solutions to improve data quality, matching, classification, and automation.
• Apply advanced analytics and generative AI to enhance data enrichment and ongoing data maintenance.
• Drive analytical projects from problem definition through deployment and ongoing monitoring, in partnership with cross‑functional teams.
• Establish and follow best practices for model governance, testing, documentation, and performance tracking.
• Build and maintain reliable data pipelines and feature workflows using distributed data technologies.
• Develop production‑ready SQL to integrate and transform structured and semi-structured data.
• Create reusable tools and components to streamline data processing, scoring, and monitoring.
• Define and track key metrics to measure model effectiveness and operational improvement.
• Partner across Data Governance, Technology, Product, and Operations to address data quality and process opportunities.
• Communicate insights through clear storytelling, visuals, and executive‑ready presentations.
• Maintain strong standards for code quality, experimentation, and documentation, with a focus on collaboration and continuous improvement.
• Stay informed on advances in machine learning, generative AI, and cloud technologies.

Benefits

• Asociacion Solidarista
• Great compensation package and bonus plan
• Core benefits including medical, dental, vision, and matching 401K
• Flexible work environment, ability to work remote, hybrid or in-office
• Flexible time off including volunteer time off, vacation, sick and 12-paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees