7 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Contractual

Job Description

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.

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