Lead Machine Learning Scientist, Manchester
Manchester, North West England 1+ months ago
Job Description
Job title: Lead Machine Learning Scientist
Location: Flexible
Role overview
Markerstudy Group have a very exciting opportunity for a Lead Machine Learning Scientist to own the development, delivery and deployment of Insurance Claims and Operations use cases.
You will have the technical support of an established machine learning function, to then create fully automated machine learning pipelines.
You will be supported by an Operations Insight function that have vast experience in the delivery, evaluation, and performance tracking of machine learningmodels.
The role will be working in an exciting, diverse and changeable environment, key stakeholders will be across Broker Services, Customer&Third Party Claims, Counter Fraud and Continuous Improvement.
Responsibilities:
Engagement with key stakeholders to understand their challenges, needs and demonstrate how advanced analytics can drive improvement, from smarter data driven decisions
For developing and maintaining best practice, covering all aspects of machine learning, ensuring policies and procedures are adhered to
Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standard
Report and communicate with the Head of Machine Learning and Head of Operations Insight
Deploy and maintain machine learning methods in a DevOps / MLOps based machine learning environment
Tune machine learning methods for optimal performance.
Deploy and maintain machine learning methods in our machine learning pipelines using robust test-driven development (TDD) coding approaches, using the SOLID software development principles.
Actively contribute to creating a culture of coding and data excellence
Lead, mentor, and coach, a small, specialized team of junior machine learning specialists and insight analysts
Create roadmaps, discover and design new projects that leverage state-of-the art machine learning techniques and capabilities, including the tuning of highly sophisticated machine learning models
Key Skills and Experience:
Previous experience of delivering Insurance Claims and Operations use cases
Substantial experience in tuning and deploying machinelearning methods
Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, Clustering, Isolation Forest, SVMs, NLP, LLMs
Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc.
Experience in creating production grade coding and SOLID programming principles, including test-driven development (TDD) approaches
Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL)
Experience in source-control software, e.g., GitHub
Ability to demonstrate that bias and ethics have been considered throughout the model build and deployment
Ability to track model performance including degradation and provide a clear and concise view on explainability
Proficient at communicating results in a concise manner both verbally and written
Behaviours:
A high level of professional/academic excellence, educated to at least a master’s level in a STEM-based or DS / ML / AI / or mathematical discipline
Collaborative and team player
Logical thinker with a professional and positive attitude
Passion to innovate and improve processes
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