Are you familiar with version control systems (e.g., Git) and agile development methodologies.

Do you always pick things up faster than everyone else?

This may be the role for you!

About the Business:

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below, https://risk.lexisnexis.com

About our Team: Our team is a small R&D team serving a large, extremely successful, socially responsible, big data business. Generally, the business is a well-oiled machine but sometimes they need a new part or a bit more oil; that’s when we get called in. We really will do whatever it takes but generally our solutions focus upon domain specific languages and automated code generation.

About the Role:

We are seeking a highly skilled and motivated Software Developer with experience using Git/Github and Java with a strong background in mathematics and machine learning to join out Entity Linking team. The ideal candidate will have a passion for developing and deploying entity linking systems that can accurately connect textual mentions to their corresponding entities in a knowledge base. This role requires advanced mathematical skills to develop and optimize algorithms for entity recognition, disambiguation, and linking.

Responsibilities:

• Develop and implement advanced entity linking algorithms using state-of-the-art techniques in machine learning.

• Design and optimize mathematical models for entity recognition, disambiguation, and linking.

• Collaborate with cross-functional teams to integrate entity linking solutions into various applications and platforms.

• Conduct research and stay updated with the latest developments in entity linking and machine learning.

• Evaluate the performance of entity linking systems using quantitative metrics and improve accuracy and efficiency.

• Write and maintain comprehensive documentation for developed software and algorithms.

Requirements :

• Advanced degree in Computer Science preferred

• Strong understanding of linear algebra, probability, and statistics.

• Proficiency in optimization techniques and algorithms.

• Experience with mathematical modeling and simulation.

• Knowledge of advanced topics such as graph theory, information theory, and computational complexity.

• Ability to apply mathematical concepts to real-world problems in entity linking.

• Strong problem-solving skills, with a desire to learn and the ability to grasp new concepts quickly. Must be able to work independently as well as in a team environment.

• Excellent communication skills, both written and verbal.

• Proficiency in Java programming language.

• Excellent communication skills, both written and verbal.

U.S. National Base Pay Range: $65,100 - $108,500. Geographic differentials may apply in some locations to better reflect local market rates.

This job is eligible for an annual incentive bonus.

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