Job Title : Data Scientist.

Work Mode : Remote.

Experience : 5- 7 Years.

Domain : Transportation.

We are seeking an experienced Senior Data Scientist with strong domain expertise in Transportation and Logistics to lead advanced analytics and optimization initiatives.

The role focuses on building scalable, production-ready data science solutions that deliver measurable business impact.

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.