Experian is the worldâs leading global information services company. During lifeâs big moments â from buying a home or a car, to sending a child to college, to growing a business by connecting with new customers â we empower consumers and our clients to manage their data with confidence. We help individuals to take financial control and access financial services, businesses to make smarter decisions and thrive, lenders to lend more responsibly, and organizations to prevent identity fraud and crime. We have 20,000 people operating across 44 countries and every day weâre investing in new technologies, talented people, and innovation to help all our clients maximize every opportunity We are very proud that FORTUNE named us one of The 100 Best Companies to Work For. In addition, for the last five years weâve been named in the 100 âWorldâs Most Innovative Companiesâ by Forbes Magazine. Experian NA Innovation Lab is a R&D unit at Experian formed with the desire to work in collaboration with Experianâs business units to enhance relationships with clients and acquire strategic datasets. ExperianÂź 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 find, develop and manage customer relationships to make their businesses more profitable. What Youâll Be Doing As a Senior Data Scientist at the Experian Innovation Lab, your role will be to research and develop innovative analytical solutions, prototype new products, and evaluate data assets. You must bring a deep understanding and extensive experience in predictive modeling, machine learning, and deep learning to this position. Key job functions include: Craft 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. Streamline data manipulation and retrieval through the design of efficient data structures and storage solutions. Innovate with tools designed for optimal data processing and information retrieval. Dissect and document vast datasets, analyzing and processing them to highlight significant patterns and insights. Solve complex business challenges by applying, developing, and inventing impactful algorithms. Ensure model excellence by validating performance scores and analyzing ROI and benefits. Articulate model processes and outcomes, documenting and presenting findings and performance metrics clearly. As part of our commitment to innovation, you will also have the unique opportunity to engage with projects involving Generative AI and Large Language Models (LLM). This separate aspect of the role allows you to explore the forefront of AI technology, applying your Data Science skills to develop solutions that leverage the latest in AI research and applications. Whether you are already skilled in AI or eager to learn, this opportunity will enable you to expand your technical repertoire and contribute to cutting-edge projects that explore new horizons in the tech landscape. Basic Qualifications: Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field. 3-7 years of working experience in AI, data science, and/or predictive modeling Proficiency in multiple programming languages, including but not limited to Python, R, Java, C++, and C. Experience in deep learning (CNN, RNN, LSTM, attention models, etc.), machine learning methodologies (SVM, GLM, boosting, random forest, etc.), graph models, and/or, reinforcement learning. Experience with open-source tools for deep learning and machine learning technology such as pytorch, Keras, tensorflow, scikit-learn, pandas, etc. Experience with large data analysis using Spark (pySpark preferred) Preferred Qualifications: Experience with LLMs and the relevant tools in the Generative AI domain. Experience in developing, modifying and experimenting advanced language models Experience in developing/applying/evaluating Generative AI based tools and technology Experience with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, mongoDB, Cassandra, etc. Experience with modifying and applying advanced algorithms to address practical problems Why choose us? Our colleaguesâ health and wellbeing are a top priority for us, thatâs why our reward, benefits and wellbeing programs are designed so you can come to work feeling your very best self. Our benefits focus on health, money, and lifestyle so you can tailor your benefits to your own personal needs. Whether itâs your physical and mental wellness, getting to work or preparing for the next big milestone in your life, we have a range of flexible options to have you covered! To learn more about our culture and what itâs really like to work here, check out our interactive guide here: Could this be the role for you? Apply now to start your journey with Experian. To learn more about our culture and what itâs really like to work here, check out our LinkedIn and social media channels using the hashtags #UniquelyExperian Youtube video link: Experian Careers – Creating a better tomorrow together Find out what its like to work for Experian by clicking here ( Perks Flexible work schedule and relaxed dress code Fully remote or in-office hybrid model, depending on location Competitively priced medical and dental plans Well-rounded employer-matched 401(k) plan Free/discounted benefits and services, such as tax-free commuter passes and free credit monitoring A well-balanced work-life balance that includes generous sick and vacation time Experian is an Equal Opportunity Employer Anyone needing accommodation to complete the interview process should notify the talent acquisition partner
recurrent-neural-network scikit-learn lstm Apache Spark Support Vector Machines (SVMs) glm reinforcement-learning deep-learning Machine Learning random-forest boosting Cassandra Hadoop HBase GenAI C pandas Data Science Python MongoDB R Apache Hive C++ conv-neural-network Java TensorFlow NoSQL keras LLM PyTorch