Data Scientist II at LexisNexis applying statistical analysis and building predictive models for fraud and credit risk. Collaborating with teams to enhance existing products and provide actionable insights.
About the role
- Data Scientist joining a leading economic consultancy to implement data science solutions for business challenges and advance thought leadership in advanced analytics.
Responsibilities
- Work on client-facing projects, designing and implementing complex data science solutions, from concept to productions to solve real-world competition and regulatory challenges faced by businesses. Each project is different - one week, you might solve a data engineering challenge, which could involve mining large datasets. The next week, you may find yourself working on natural language processing using large language models, developing innovative AI applications.
- Contribute to cutting-edge research projects, advancing Compass Lexecon’s thought leadership in the application of advanced analytics to competition and finance cases.
- Conduct advanced training sessions and develop sophisticated tools to enhance how economists work with data.
Requirements
- Master’s degree in data science, computer science, applied mathematics, statistics, machine learning, economics, or operations research.
- At least 2 years of professional data science experience, with a proven track record of translating business problems into data science solutions.
- Proficiency in Python, R, and SQL, with experience developing production-level code and working effectively with relevant libraries and frameworks, as well as hands-on proficiency with NoSQL databases such as MongoDB.
- Possess practical experience with a range of data science methods and concepts, such as data engineering workflows, machine learning, natural language processing, with the ability to quickly learn new tools as needed.
- Hands-on experience with cloud computing platforms (Azure, AWS, or GCP) and container technologies (such as Docker) in collaborative project environments.
- Solid understanding of data engineering principles including data modelling, ETL processes, and building data pipelines.
- Strong organizational skills, able to independently manage multiple projects and deliverables on time.
- Excellent teamwork and communication skills, with demonstrated ability to share knowledge and present findings clearly to both technical and non-technical colleagues.
Benefits
- Equal opportunities employer
- Diverse teams considered and respected
Job title
Job type
Experience level
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Not specified
Degree requirement
No Education Requirement
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