Sr. Data Scientist
Core
Develop, deploy, and scale machine learning and AI solutions for fleet analytics, logistics optimization, and operational decision-making.
Role type
Senior IC machine learning engineer (logistics/fleet analytics)
Builds
Production-grade ML models, real-time streaming pipelines, and AI-driven decision systems for fleet operations
Domain
Transportation logistics and fleet management
Deliverable
production ML models
Required skills
Python, SQL, Google Cloud Platform (Vertex AI, BigQuery), Kafka, RisingWave, time-series forecasting, anomaly detection, optimization, LLMs (RAG)
Preferred skills
Azure, AWS, Databricks, geospatial ML, graph ML, computer vision, KAG, CAG
Technologies
Google Cloud, Kafka, RisingWave, BigQuery, AlloyDB, Snowflake, Vertex AI, PyTorch, TensorFlow, XGBoost, LightGBM, OpenAI, Hugging Face
Responsibilities
Design and deploy ML models for route optimization, ETA prediction, and predictive maintenance; Build anomaly detection and forecasting models for vehicle health and demand; Develop batch and real-time ML pipelines with low-latency inference; Integrate LLMs for conversational analytics and RAG systems; Operate MLOps workflows for model training, deployment, and monitoring; Build and optimize end-to-end data pipelines; Design scalable analytical data models; Build dashboards for stakeholders.
Seniority
Senior, hands-on IC