Data Scientist Location : Onsite DFW Airport, TX 75261 Duration: 3-4 Weeks Contract Note: Kindly Apply if you're willing to work on W2 and local to Dallas, TX. We are seeking an experienced and forward-thinking Data Scientist with deep expertise in statistical modelling, deep learning, machine learning engineering, and streaming data analytics to support digital transformation in airport operations. This role is central to building AI-powered solutions that optimize resource movement, enhance passenger flow, and enable real-time operational decisions. The ideal candidate will have hands-on experience in deploying machine learning models on Azure Cloud and working with high-velocity airport data. Key Responsibilities: • Design and implement advanced statistical models and deep learning architectures (e.g., LSTM, CNNs, Transformers) to solve complex problems related to passenger behavior, baggage handling, gate allocation, and delay prediction. • Build and deploy machine learning models on Azure Machine Learning for use in real-time operational systems and digital products. • Work with streaming data sources to develop predictive models that support real-time airport decision-making. • Collaborate with AI Engineers and Product teams to ensure smooth integration of models into Azure-based production environments using APIs, containers (Docker), and MLOps pipelines. • Develop time-series forecasting, resource demand prediction, and simulation-based models for terminal operations and airside logistics. • Conduct feature engineering, model evaluation, and hyperparameter tuning to ensure performance and scalability of ML models. • Create visualizations and decision dashboards that translate model outputs into actionable insights for operations teams and airport stakeholders. • Maintain and document model lifecycle, version control, and ensure alignment with airport data governance and compliance frameworks. Required Qualifications: Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or a related field. • 7 + years of experience in applied data science roles, including deep learning and machine learning deployment. • Proficiency in Python and key libraries (TensorFlow, PyTorch, Scikit-learn, StatsModels, Pandas, NumPy). • Strong experience building and deploying ML models in Azure cloud environments, using Azure ML, Azure Data Factory, and Azure Databricks. • Hands-on experience with streaming data processing using tools such as Azure Stream Analytics, Kafka, or Spark Structured Streaming. • Solid knowledge of statistical analysis, probabilistic modeling, clustering, classification, and regression techniques. • Expertise in SQL and working with relational and non-relational data sources. PriceSenz is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, or disability.