Senior Software Engineer

RELX

. Design, implement, and maintain neural network models and enterprise-wide model governance frameworks, standards, and controls for machine learning and linking solutions .

Posted 11/10/2026full-timeUnited StatesSenior💰 $95,300 - $158,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing neural network models and model governance frameworks, with a strong focus on model validation, performance assessment, and risk management. Proficient in statistical analysis and communication of complex model behaviors to diverse stakeholders.

Highest-signal resume keywords

Neural Network ModelsModel GovernanceModel Validation MethodologiesStatistical AnalysisCloud-Based Platforms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData SciencePredictive AnalyticsStatistical Modeling TechniquesPerformance MeasurementDrift DetectionBias AssessmentExplainability TechniquesJavaPython

Soft Skills

Analytical SkillsProblem-Solving SkillsCommunication SkillsPresentation SkillsInfluencing Skills

Tools & Technologies

AzureDatabricksSparkCosmos DBData Analysis Tools

Industry Keywords

AI GovernanceResponsible AIModel Risk ManagementModel Lifecycle ProcessesGovernance Metrics

Tech Stack

Tools & technologies

AzureCloudJavaPythonSparkSQL

About the role

Key responsibilities & impact

Design, implement, and maintain neural network models and enterprise-wide model governance frameworks, standards, and controls for machine learning and linking solutions
Lead model validation and review activities, including performance assessment, precision analysis, explainability evaluation, bias testing, and risk identification
Establish and monitor model lifecycle processes covering development, testing, deployment, monitoring, retraining, and retirement
Develop governance metrics, dashboards, and reporting to provide visibility into model performance, drift, risk exposure, and business impact
Partner with data scientists, software engineers, architects, and business stakeholders to embed governance requirements throughout the model development lifecycle
Create and maintain model documentation, validation reports, audit artifacts, governance approvals, and regulatory evidence
Evaluate model performance using statistical analysis, precision and recall measurements, confidence scoring, explainability techniques, and business outcome monitoring
Lead investigations into model degradation, unexpected behavior, accuracy declines, and governance exceptions, recommending mitigation strategies and corrective actions
Establish controls and monitoring processes to identify data drift, concept drift, and operational risks affecting model quality
Communicate governance findings, model risks, validation outcomes, and recommendations to technical teams, executive leadership, auditors, and business stakeholders
Drive continuous improvement of model governance processes, tools, standards, and best practices across the organization

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Machine Learning, Engineering, or a related technical discipline
10+ years of experience in machine learning, data science, analytics, model development, model validation, or AI governance
Strong understanding of neural network models, machine learning algorithms, statistical modeling techniques, predictive analytics, and AI systems
Experience establishing or operating model governance, model risk management, AI governance, or Responsible AI programs
Strong knowledge of model validation methodologies, performance measurement, drift detection, bias assessment, and explainability techniques
Experience with cloud-based platforms including Azure, Databricks, Spark, Cosmos DB, and large-scale data processing technologies
Hands-on experience with Java, Python, SQL, machine learning frameworks, and data analysis tools
Experience developing dashboards and automated monitoring solutions for model performance and governance metrics
Strong analytical and problem-solving skills with the ability to evaluate complex technical and business risks
Strong communication and presentation skills, with the ability to explain complex model behavior and governance findings to both technical and non-technical audiences
Ability to influence technical direction, governance strategy, and enterprise decision-making across multiple organizations

Benefits

Comp & perks

Annual incentive bonus
Country specific benefits
Accommodation or adjustment support during the hiring process