Data Scientist - Experian Innovation Lab

Employment Type: Full-time Location Type: Remote Salary: Not Specified

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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.

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Position Overview

The Experian Innovation Lab is a research and development unit at Experian, formed with the desire to work in collaboration with Experian's teams to enhance relationships with clients and acquire strategic datasets. Using our comprehensive understanding of individuals, markets, and economies, we help organizations develop customer relationships to make their businesses more profitable.

As a Data Scientist at the Experian Innovation Lab, you will help develop analytical solutions, contributing to product prototypes, and helping evaluate data assets. You will bring experience in predictive modeling, machine learning, and deep learning to this position. You will report into the VP of Data Science.

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Responsibilities

• 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.
• 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.
• Articulate model processes and outcomes, documenting and presenting findings and performance metrics.

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Qualifications

• Education: Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field.
• Experience: 1 or more years of experience in AI, data science, or predictive modeling.
• Programming: Proficiency in at least one programming language, with coding skills in Python.
• Machine Learning & Deep Learning: Experience with deep learning (CNN, RNN, LSTM, attention models), machine learning methodologies (SVM, GLM, boosting, random forest), graph models, or reinforcement learning.
• Tools & Libraries: Experience with open-source tools for deep learning and machine learning technology such as PyTorch, Keras, TensorFlow, scikit-learn, pandas.
• Big Data: Experience with large data analysis using Spark (pySpark preferred).
• Generative AI: Experience with LLMs and the relevant tools in the Generative AI domain. Experience developing advanced language models and applying Generative AI-based tools.
• Big Data Technologies: Experience with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, MongoDB, Cassandra.
• Algorithm Application: Experience modifying and applying advanced algorithms to address practical problems.

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Additional Information & Benefits

• Benefits:
  • 20 vacation days to start (along with 12 paid holidays).
  • Great compensation package and comprehensive benefits package.
  • Bonus of 20%.
  • Flexible work schedule and relaxed dress code.
• Culture: Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition.

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