Building innovative solutions; enabling safer workplaces for everyone.
We’ll create a safer working world, building software to support a global network of responsible buyers, suppliers and partners.
We take the pain out of compliance for over 50,000 organisations globally, helping them protect their people, their operations, and the planet.
Keeping our network of hiring clients, suppliers, and contractors compliant with the standards that matter most, from health and safety and sustainability to ethical behaviour by building best in class solutions.
Veriforce is seeking a data scientist with hands-on experience building models to power workflows for business applications and internal processes. You will join a growing team of talented data modeling, data engineering, AI engineers, and DevOps engineers, to expand our platforms to integrate with LLMs, MCPS, APIs, and enterprise data. Your work will help shape the way our clients and contractors get to work faster, stay compliant, and come home safely every day.
- Design, develop, and deploy machine learning models for risk scoring, compliance prediction, churn analysis and contractor performance analytics.
- Build and deploy Large Language Models (LLMs) based solutions for text data insights, anomaly detection, and automated compliance checks.
- Collaborate with engineering and product teams to integrate models into production systems hosted on AWS and Azure.
- Utilize Microsoft Fabric for data ingestion, transformation, and feature engineering.
- Implement best practices for model monitoring, retraining, and performance optimization.
- Participate as an integral member of a cross functional team using agile methodologies
- Work in an Agile based SDLC that embraces the principles of transparency, cooperation, decomposing work, and rapid iteration
- Stay current with emerging technologies in AI/ML, predictive analytics, and supply chain risk management.
- Ability to communicate with non-engineers about how technology is solving business needs. Including demonstrating features for feedback.
- Education: Bachelor’s or master's in data science, Computer Science, Statistics, or related fields.
- Experience:
- Proven experience with Python, SQL, and ML frameworks (e.g., TensorFlow, PyTorch, Jupyter Notebooks).
- Familiarity with AWS services (S3, SageMaker, Lambda) and Microsoft Fabric.
- Strong understanding of predictive modeling, NLP, and LLM architectures.
- Excellent problem-solving skills and ability to communicate complex concepts to non-technical stakeholders.
- Exceptional communication skills, being able to translate business requirement into technical output, and the ability to relay outcomes back to the appropriate audience.
