AI/Scoring Engineer (ML, MLOps, Azure, Quantexa) - London and remote - 11 months +
Posted Today by Octopus Computer Associates
£512 Per day
Inside
Hybrid
London and remote, UK
Summary: The AI/Scoring Engineer role focuses on designing, building, and maintaining machine learning models and pipelines on the Azure platform, specifically for the Quantexa Fraud platform program. The position requires a blend of technical expertise in machine learning and collaboration with cross-functional teams. The role is hybrid, requiring on-site presence in London 2-3 days a week. Candidates must be eligible for BPSS and work through an umbrella company, as the position is classified as inside IR35.
Key Responsibilities:
- Analyse business requirements and support the Quantexa platform.
- Build and deliver AI systems as an individual contributor and in teams.
- Design and maintain solutions using a hypothesis-based approach, collaborating with technical teams.
- Deliver results rapidly in a fast-paced environment.
- Communicate complex concepts succinctly to stakeholders.
- Extract meaning from data using statistical and machine learning methods.
- Collect, clean, and organise data to generate insights for business problems.
- Explain and present analytical results.
- Analyse defects and provide fixes.
- Provide release notes for deployments and support release activities.
- Maintain up-to-date technology skills across the platform.
Key Skills:
- Exposure to fraud, financial crime, customer insights, or compliance-based projects.
- Strong knowledge of statistics, deep learning, and machine learning techniques.
- Experience with MLOps, model deployment, CI/CD, and unit testing.
- Experience in building ML pipelines and feature engineering.
- Knowledge of model governance, including explainability and documentation.
- Desirable knowledge of Scala, Python, Apache Spark, and Azure platform.
- Strong knowledge of SQL.
- Strong analytical, machine learning, and deep learning skills.
Salary (Rate): £511.8 per day
City: London
Country: UK
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
AI/Scoring Engineer (ML, MLOps, Azure, Quantexa) - London and remote - 11 months +/RATE: £511.8 per day inside IR35
One of our Blue Chip Clients is urgently looking for an AI/Scoring Engineer (ML, MLOps, Azure, Quantexa).
For this role you will need to be onsite in London 2-3 days per week.
Please find some details below:
CONTRACTOR MUST BE ELIGIBLE FOR BPSS
MUST BE PAYE THROUGH UMBRELLA
Role Description:
ROLE PURPOSE
The purpose of the AI engineer is to design, build, unit test and maintain ML model and ML pipelines for Projects and Programmes on Azure Platform. This role will be purposed for Quantexa Fraud platform programme, Quantexa certified scoring engineer is preferred.
KEY ACCOUNTABILITIES
Analyse business requirements and support and maintain Quantexa platform.
Build and deliver AI systems as an individual contributor and in teams
Help design and maintain a solution using a rigorous hypothesis-based approach, partner with cross functional technical teams including solution architect and data engineers, and execute the development with focus on impact
Rapidly and iteratively deliver results in a fast-paced environment with skills creative to pivot quickly for alternative solutions
Break down complex concepts into succinct components which can be easily communicated to range of stakeholders
Able to extract meaning from and interpret data, which requires both tools and methods from statistics and machine learning, as well as being human
Able to collect, clean and organise data, to generate insights from data to solve business problems and create business value.
Explaining and presenting analytical results
Analyse defects and provide fixes
Provide release notes for deployments
Support Release activities
Problem solving attitude
Keep up to date with new skills - Develop technology skills in other areas of Platform
FUNCTIONAL/TECHNICAL SKILLS
Skills and Experience:
Exposure to Fraud, financial crime, customer insights or compliance-based projects that utilize detection and prediction models
Strong knowledge of statistics, deep learning, machine learning, K-NN, random forest, ensemble methods etc
Experience with MLOps including model deployment, CI/CD and unit testing. (GIT, Azure devops etc)
Experience in building ML pipelines, feature engineering and ability to handle large dataset for business insights.
Experience with model governance including explainability, observability and documentations
Scala and Python knowledge desirable, Apache Spark, Azure platform knowledge is a plus
Strong knowledge of SQL
Strong Analytical, machine learning and deep learning skills
Please send CV for full details and immediate interviews. We are a preferred supplier to the client.