Senior Data Scientist

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November 10

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PrePass

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Transport

PrePass is North America’s most comprehensive and widely used service for weigh station bypass and toll payment. They offer solutions for private fleets, for-hire carriers, and owner-operators, tailored to streamline operations and reduce costs. The service aims to save time, reduce fuel consumption, and enhance safety through their extensive weigh station bypass network and simplified toll management with advanced technology and support. Their platform includes multiple technology options to improve fleet efficiency and provides insights for operational optimization and risk management. Founded in 1993 and headquartered in the U. S. A. , PrePass is known for innovative services and exceptional customer support.

201 - 500 employees

Founded 1995

🚗 Transport

📋 Description

• Design, train, and evaluate predictive and optimization models using statistical, machine learning, and deep learning techniques. • Build and deploy models for classification, regression, clustering, and anomaly detection. • Develop time series forecasting models for churn prediction and demand forecasting. • Balance R&D prototyping with production-grade model development. • Partner with data architects and engineers to source, clean, and transform large datasets from the Fabric data lakehouse and warehouse environments. • Create reusable data pipelines and feature stores for model training and scoring. • Ensure model reproducibility, explainability, and integration into downstream reporting or applications. • Use Python extensively with libraries such as scikit-learn, pandas, numpy, statsmodels, seaborn, and matplotlib. • Work with SQL and T-SQL for data manipulation and analysis. • Create compelling visualizations and dashboards using Power BI including DAX measures. • Partner with BI analysts, data engineers, and architects to understand business needs. • Translate complex modeling outcomes into actionable business recommendations. • Present findings and model outcomes to non-technical stakeholders across Product, Operations, and Leadership. • Contribute to the development of scalable data science infrastructure and best practices.

🎯 Requirements

• **Qualifications ****Required** • - Bachelor’s degree in computer science, statistics, mathematics, machine learning, or equivalent quantitative field. (Master’s or PhD preferred.) • - 5+ years of experience in building machine learning models in business contexts. • - Proven track record of deploying models in production environments. • - Strong collaboration and communication skills in dynamic, cross-functional teams. • **Preferred** • - Proficiency in Microsoft cloud technologies, especially Fabric. • - Experience building ML pipelines with MLOps features including preprocessing, training, model deployment, monitoring/retraining, and CICD. • - Experience working with GPS telemetry data including latency, gaps, and error handling. • - Familiarity with geospatial data science including spatial joins, clustering, ArcGIS GeoAnalytics, and geohashing.

🏖️ Benefits

• **How We Will Take Care of You** • - Robust benefit package that includes medical, dental, and vision that start on date of hire. • - Paid Time Off, to include vacation, sick, holidays, and floating holidays. • - 401(k) plan with employer match. • - Company-funded “lifestyle account” upon date of hire for you to apply toward your physical and mental well-being (i.e., ski passes, retreats, gym memberships). • - Tuition Reimbursement Program. • - Voluntary benefits, to include but not limited to Legal and Pet Discounts. • - Employee Assistance Program (available at no cost to you). • - Company-sponsored and funded “Culture Team” that focuses on the Physical, Mental, and Professional well-being of employees. • - Community Give-Back initiatives. • - Culture that focuses on employee development initiatives.