Quantexa AI/Scoring Engineer (ML, MLOps, Azure) - London and remote - 11 months +

Quantexa AI/Scoring Engineer (ML, MLOps, Azure) - London and remote - 11 months +

One of our Blue Chip Clients is urgently looking for a Quantexa AI/Scoring Engineer (ML, MLOps, Azure)

You MUST have 3-5 years+ of Quantexa experience

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.