Data Scientist

Summary

Join Experian's Innovation Lab as a Sr. Data Scientist and contribute to developing analytical solutions, product prototypes, and evaluating data assets. You will leverage your expertise in predictive modeling, machine learning, and deep learning to extract insights from diverse data sources. Responsibilities include crafting advanced machine learning solutions, refining data manipulation, innovating with data processing tools, and documenting datasets. You will also solve complex challenges through algorithm development and ensure model excellence by validating performance. The role requires articulating model processes and presenting findings. Experian offers a competitive compensation package, flexible work schedule, and a comprehensive benefits package.

Requirements

• Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field
• 1 or more years of experience in AI, data science, or predictive modeling
• Proficiency in at least one programming language, with coding skills in Python
• Experience with 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 Spark (pySpark preferred)
• Experience with LLMs and the relevant tools in the Generative AI domain
• Experience developing advanced language models
• Experience applying Generative AI-based tools
• 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

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

Benefits

• 20 vacation days to start (along with 12 paid holidays)
• Great compensation package and comprehensive benefits package, with a bonus of 20%
• Flexible work schedule and relaxed dress code