Data Scientist - Fleet Analytics & MLOps

Charger Logistics Inc.; Brampton; On-site; CAD 100,000 - 140,000; Full time

Job summary

Charger Logistics Inc. is leveraging data science to optimize fleet operations across North America.

The role focuses on building production-grade ML models for route optimization, ETA, fuel efficiency, and maintenance, with real-time analytics on cloud platforms including Google Cloud, Kafka, and RisingWave. You will implement end-to-end data pipelines, integrate LLMs for conversational insights, and manage ML workflows with Vertex AI Tools, BigQuery, and Snowflake, collaborating across teams

Qualifications

• Bachelor's degree in Data Analytics, Statistics, Mathematics, or Computer Science required.
• 4+ years of hands-on data science and ML/AI delivering production-grade solutions.
• Strong experience with Python and ML libraries (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM).
• Advanced SQL with CTEs, window functions, and optimization.
• Hands-on with Google Cloud (Vertex AI, BigQuery) and Snowflake; streaming with Kafka.
• Experience with ETL/orchestration tools (Matillion, Airflow, Cloud Composer).
• Knowledge of LLMs, geospatial/graph ML, GPS data, and RAG approaches.

Responsibilities

• Design, develop, and deploy production-grade ML models for fleet optimization (route, ETA, fuel efficiency, capacity, maintenance, driver behavior).
• Build anomaly detection, forecasting, and time-series models for vehicle health and demand fluctuations.
• Develop batch and real-time ML pipelines with low-latency inference using Kafka, RisingWave, and cloud services.
• Integrate LLMs for conversational analytics and retrieval-augmented generation (RAG).
• Operate MLOps on Google Cloud (Vertex AI Pipelines, Feature Store, Model Registry) for training, deployment, monitoring, drift detection.
• Build end-to-end data pipelines for analytics using BigQuery, Dataflow, Dataproc, Vertex AI, Cloud Functions, Pub/Sub, Cloud Composer.
• Design scalable analytical data models in BigQuery, AlloyDB PostgreSQL, Snowflake; optimize SQL-based features and clustering.
• Perform exploratory data analysis to uncover trends and insights; build dashboards for stakeholders.
• Collaborate with cross-functional teams to translate business problems into data science solutions.
• Support best practices in model development, experimentation, documentation, and data governance.

Skills

Python

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

XGBoost

LightGBM

SQL

BigQuery

Cloud platforms

Kafka

RisingWave

MLOps

Education

Bachelor's degree in Data Analytics, Statistics, Mathematics, or Computer Science

Tools

Google Cloud

Vertex AI

BigQuery

Dataflow

Dataproc

Vertex AI Pipelines

Feature Store

Model Registry

Kafka

RisingWave

Snowflake

Airflow

Cloud Composer

Matillion

GCP services

Kag

Job description

Charger Logistics Inc. is leveraging data science to optimize fleet operations across North America.

The role focuses on building production-grade ML models for route optimization, ETA, fuel efficiency, and maintenance, with real-time analytics on cloud platforms including Google Cloud, Kafka, and RisingWave. You will implement end-to-end data pipelines, integrate LLMs for conversational insights, and manage ML workflows with Vertex AI Tools, BigQuery, and Snowflake, collaborating across teams