Senior Data Scientist, Innovation Lab - Remote

Job Description

Job Description

Company Description

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 accomplish 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.

Job Description

Experian Innovation Lab is a research and development unit at Experian formed with the desire to work in collaboration with Experian's departments to enhance relationships with clients and acquire strategic datasets. Experian® is a global leader in providing information, analytical tools and marketing services to organizations and consumers to help manage the risk and reward of commercial and financial decisions. Using our comprehensive understanding of individuals, markets and economies, we help organizations develop customer relationships to make their businesses more profitable.

As a Senior Data Scientist at the Experian Innovation Lab, your role will be to research and develop analytical solutions, prototype new products, and evaluate data assets. You must bring an experience in predictive modeling, machine learning, and deep learning to this position. You will report into the Sr. Principal Data Scientist

You'll have opportunity to :

• Create advanced machine learning analytical solutions to extract insights from diverse structured and unstructured data sources.
• Unearth data value by selecting and applying the right machine learning, deep learning and processing techniques.
• Refine data manipulation and retrieval through the design of efficient data structures and storage solutions.
• Innovate with tools designed for data processing and information retrieval.
• Dissect and document vast datasets, analyzing them to highlight patterns and insights.
• Solve complex challenges by developing impactful algorithms.
• Ensure model excellence by validating performance scores and analyzing Return on investment and benefits.

Qualifications

Additional Information

Benefits / Perks :

At Experian, our people and culture set us apart. We're deeply committed to creating an environment where everyone feels they belong and can excel. From inclusion and authenticity to work / life balance, development, wellness, collaboration, and recognition, we focus on what truly matters. Our people-first approach has earned us global recognition : World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ 2025 in 26 countries, and Glassdoor Best Places to Work 2024, among others.

Want to see what life at Experian is really like? Explore Experian Life on social or visit our Careers Site.

Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. You will be also eligible for a variable pay opportunity.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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