Senior Data Scientist, Innovation Lab - Remote - Remote Staffing : Job Details

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.

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. 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:

• Master's Degree or higher in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field.
• 2+ years of experience in AI, data science, or predictive modeling.
• Proficiency in multiple programming languages, including Python.
• Experience in deep learning (CNN, RNN, LSTM, attention models), machine learning methodologies (SVM, GLM, boosting, random forest), graph models, or reinforcement learning.
• Experience with open-source tools for deep learning and machine learning technology such as pytorch, Keras, tensorflow, scikit-learn, pandas.
• Experience with large data analysis using pySpark.
• Experience with LLMs and the relevant tools in the Generative AI domain.
• Experience with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, mongoDB, Cassandra.
• Experience modifying and applying advanced algorithms to address practical problems.
• Experience with online, mobile marketing analytics.
• Experience with GPU programming.

Benefits/Perks:

• 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.

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. 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. 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.