Data Scientist

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 application 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.

 

· 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.

· Design, develop, and deploy machine learning models for risk scoring, compliance prediction, and contractor performance analytics.

· Build and fine-tune Large Language Models (LLMs) for text-based insights, anomaly detection, and automated compliance checks.

· Collaborate with engineering and product teams to integrate models into production systems hosted on AWS.

· Utilize Microsoft Fabric for data ingestion, transformation, and feature engineering.

· Conduct exploratory data analysis (EDA) and develop dashboards to communicate insights to stakeholders.

· Implement best practices for model monitoring, retraining, and performance optimization.

· 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.

· Ability to methodically debug problems to resolve issues at the root.

· Produce code that adheres to coding standards of consistency, readability, testability, security, and maintainability. Ability to leverage AI coding assistance (i.e. Copilot, etc.).

· Education: Bachelor’s or master's in data science, Computer Science, Statistics, or related fields.

· 5+ years in data science or machine learning roles.

· 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.

· Experience in risk modeling, compliance analytics, or supply chain data.

· Knowledge of MLOps and CI/CD pipelines for ML deployment.

· Familiarity with data governance and regulatory compliance frameworks.