Lead Machine Learning Engineer

Join our team to redefine the landscape of financial services through the lens of Risk Intelligence Innovation. We're looking for a Machine Learning Engineer who is ready to dive into the dynamic fields of digital identity, and fraud. You will be crucial in shaping the future of these areas.

We are searching for a candidate who is not only passionate about risk intelligence but also brings a wealth of experience in handling complex, large-scale projects. Your role will involve collaboration with both internal and external stakeholders, demanding a high level of proficiency in communication and teamwork.

You will report directly to the Director of Data Science and play a key role in guiding the development of ML and AI technology within the organization.

Your responsibilities will include the analysis of complex datasets, designing algorithms and models to detect and prevent financial crimes, and contributing to the design of ML, AI and Data infrastructure in line with LSEG Risk Intelligence' objectives.

Your expertise in Data Science and ML and AI related technologies will be pivotal in steering the direction of our development efforts.

This role is not just a job, but a journey into the future of risk intelligence, where your skills and insights will contribute significantly to our innovative endeavors.

About You – experience, education, skills, and accomplishments

• Bachelor's degree in computer science, data science, mathematics, or a related field
• Master’s degree in computational linguistics, data analytics, or similar will be advantageous
• 5 years of experience as a machine learning engineer
• Advanced proficiency with Python, Java, and R code writing
• Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture
• In-depth knowledge of mathematics, statistics, and algorithms
• Superb analytical and problem-solving abilities
• Great communication and collaboration skills
• Work with regular software development tooling such as Azure DevOps, Git, CLI, Visual Studio Code

It would be great if you have. . ..

• Excellent understanding of Data Science Theory, LLMs, ML, NLP, and statistical methodologies in a data analytics environment.
• Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation.
• Relevant certifications in AI, ML or Data Engineering from Microsoft
• Understanding of all phases of a complete Data Science Lifecycle

What will you be doing in this role?

• Prototype, benchmark and deploy algorithms to improve performance.
• Design scalable and reliable data pipelines to productionize and monitor models
• Develop classification and prediction algorithms to detect data trends
• Identify, research, and analyze new data sources to improve model accuracy
• Work cross-functionally with data engineers, data analysts and software engineers to continuously improve performance
• Develop production code to run locally and in the cloud - debug and tune production systems
• Validate experimentation code developed by Data Scientists and deploy using Azure ML services and MLOps
• productionizing a model, with a strong focus on software development practices such as DevOps, CI/CD, monitoring and the right infrastructure for scaling the solution
• Consulting with managers to determine and refine machine learning objectives
• Running tests, performing statistical analysis, and interpreting test results
• Documenting machine learning processes
• Keeping abreast of developments in machine learning

About the team

• This is a new Data Science innovation team within the Risk Intelligence Engineering function.
• Our engineers use Machine Learning to solve problems along the entire Lifecycle of Innovation, with a strong focus on new capabilities and approaches to existing problems.
• Algorithms to detect fraud, predicting risk and outcomes are just a few of the ways our team is fostering productivity of our customers who lead innovation in the world. 
• We are a global team reporting into the Head of Risk Intelligence in the US. The team culture is all about openness & collaboration with a focus on excellence and value adding innovation. We have a tradition of also being a source of innovation ourselves, based on deep domain knowledge, so being creative and entrepreneurial is very much encouraged.

LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.

Our purpose is the foundation on which our culture is built. Ou