Senior Data Scientist

Role:

Senior Data Scientist Work Mode:

Remote Year of Experience:

5 - 7 Years

Good To Have Skills:

Communication Must Have Skills:

Data science, Transportation, Optimization

External Description

We are seeking a highly experienced and domain-focused Senior Data Scientist to lead advanced analytics and machine learning initiatives with transportation and logistics operations experience. The ideal candidate will have deep expertise applying data science methodologies to solve complex transportation challenges, a proven ability to leverage PySpark on Azure/Databricks for scalable solutions, and a track record of delivering measurable business impact.

Key Responsibilities Domain Leadership & Modeling: Lead the design, development, and deployment of sophisticated predictive and prescriptive models specifically forthe transportation domain (e.g., route optimization, demand forecasting, predictive maintenance for fleet, network efficiency, logistics planning, and anomaly detection). Big Data & Cloud Implementation: Architect and implement scalable machine learning learning workflows and ETL processes utilizing PySpark within the Azure ecosystem (e.g., Azure Synapse, Azure Data Lake Storage). Databricks Expertise: Serve as the technical expert for developing and executing data science notebooks and ML pipelines on Databricks, ensuring optimized performance and cost efficiency. Collaboration & Strategy: Partner closely with operations, engineering, and business intelligence teams to identify high-impact analytical opportunities and translate complex business problems into clear data science initiatives. MLOps & Production: Establish and maintain robust MLOps practices, including model versioning, continuous integration/continuous deployment (CI/CD), and monitoring of production models deployed in the cloud environment. Data Analysis & Storytelling: Conduct in-depth analysis of transportation data, providing actionable insights and communicating complex technical findings and their business value to both technical and executive stakeholders. Qualifications Experience: 5+ years of progressive professional experience in a Data Scientist or a Machine Learning Engineer role. Domain Expertise: Mandatory 3+ years of experience working specifically within the Transportation, Logistics, Supply Chain, or Fleet Management industry.

Technical Stack: Expert proficiency in Python and its data science ecosystem (e.g.,pandas, NumPy, scikit-learn, TensorFlow/PyTorch). Advanced proficiency in PySpark for large-scale data processing and machine learning model development. Expert experience with Azure cloud services relevant to data science (e.g., Azure ML, Azure Data Factory, Azure Data Lake Storage, Azure Synapse). Mandatory expertise working with Databricks (Delta Lake, MLflow) for model training, tracking, and deployment. Strong SQL skills for data querying and manipulation. Education: Bachelor's or Master's degree in a quantitative field (e.g., Data Science, Computer Science, Operations Research, Engineering).