Data Scientist

Job Title: Data Scientist

Work Mode: Remote

Experience: 5–7 Years

Domain: Transportation

Transportation and Logistics

Key Responsibilities:

• Design, develop, and deploy predictive and prescriptive models for transportation use cases such as route optimization, demand forecasting, fleet predictive maintenance, logistics planning, and anomaly detection.
• Build scalable data pipelines, ML workflows, and ETL processes using PySpark within the Azure ecosystem.
• Develop and optimize data science notebooks and ML pipelines on Databricks, ensuring performance and cost efficiency.
• Collaborate with operations, engineering, and BI teams to translate business problems into data science solutions.
• Implement and maintain MLOps practices, including model versioning, CI/CD, and production monitoring.
• Analyze large-scale transportation data and communicate insights effectively to technical and business stakeholders.

Must-Have Skills:

• Data Science
• Transportation domain expertise
• Optimization techniques

Good-to-Have Skills:

• Strong communication and stakeholder management skills

Technical Skills:

• Advanced Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch).
• Strong PySpark experience for large-scale data processing and ML.
• Expertise in Azure services (Azure ML, Azure Data Factory, Azure Data Lake Storage, Azure Synapse).
• Mandatory hands-on experience with Databricks (Delta Lake, MLflow).
• Strong SQL for data querying and manipulation.

Qualifications:

• 5+ years of experience as a Data Scientist or Machine Learning Engineer.
• Mandatory 3+ years of experience in Transportation, Logistics, Supply Chain, or Fleet Management domains.

Additional Skills:

• Experience working with unstructured and distributed data (telematics, GIS/location data, sensor data).
• Proven ability to deliver production-grade ML solutions with measurable business outcomes.