Charger Logistics Inc.
Transportation
DataScientist
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Scientist at Charger Logistics Inc.. Skills: Machine learning, Google Cloud, Python, SQL. Develop ML models for fleet optimization. Build anomaly detection, forecasting, time-series models”
Industry & Context.
Problem-solving skills
What They're Looking For.
Must Have
Bachelor’s degree or equivalent in Data Analytics, Statistics, Mathematics, or Computer Science, 4+ years of hands-on experience in data science and machine learning, experience in Python, Advanced SQL skills, Hands-on experience with Google Cloud, Experience with streaming platforms, Knowledge of anomaly detection, Knowledge of time-series forecasting, Knowledge of optimization, Knowledge of applied statistical modeling, Experience deploying and monitoring ML models in production, Experience working with ETL/orchestration tools
Nice to Have
Google Cloud Professional Data Engineer or Machine Learning Engineer certification, SnowPro® Advanced: Data Scientist certification, Experience with LLMs, Experience with geospatial or graph ML, Experience with computer vision, Experience with GPS data analysis, Experience with Azure, Experience with AWS, Experience with GCP, Experience with Databricks, Experience with multi-cloud deployments
What You'll Do.
Develop ML models for fleet optimization
Build anomaly detection
Develop batch and real-time ML pipelines
Integrate large language models
Operate MLOps workflows on Google Cloud
Build and optimize end-to-end data pipelines
Design scalable analytical data models
Perform exploratory data analysis
Build dashboards and visualizations
Collaborate with cross-functional teams
Support best practices in model development
How You'll Work.
Team & Collaboration
Collaborate with cross-functional teams to translate business problems into robust data science solutions.
Communication Scope
Excellent communication skills
Full Job Description
Charger Logistics Inc. is a leading asset-based transportation company with over 20 years of experience delivering innovative logistics solutions. We have evolved into a world-class transport provider and continue to expand across North America. We invest in our people, fostering an environment where learning, growth, and career advancement are encouraged. As an entrepreneurial organization, we value initiative, creativity, and forward-thinking strategies. We are looking for a **Data Scientist** to develop, deploy, and scale machine learning (ML) and AI solutions for fleet analytics, logistics optimization, and operational decision-making. This is a hands-on role focusing on production-grade ML, real-time and streaming analytics, and AI-driven decision systems built on cloud platforms, including Google Cloud, Kafka, and RisingWave. **Responsibilities:** * Design, develop, and deploy production-grade ML models for fleet optimization, including route optimization, ETA prediction, fuel efficiency, capacity planning, predictive maintenance, and driver behavior analysis. * Build anomaly detection, forecasting, and time-series models to monitor vehicle health, trip deviations, fuel theft, and demand fluctuations. * Develop batch and real-time ML pipelines with low-latency inference using Kafka, RisingWave, and cloud services. * Integrate large language models (OpenAI, Google MCP, Ollama, Hugging Face) for conversational analytics, automated insights, and retrieval-augmented generation (RAG) systems. * Operate MLOps workflows on Google Cloud using Vertex AI Pipelines, Feature Store, and Model Registry, supporting model training, deployment, monitoring, and drift detection. * Build and optimize end-to-end data pipelines for analytics and ML using BigQuery, Dataflow, Dataproc, Vertex AI, Cloud Functions, Pub/Sub, and Cloud Composer (Airflow). * Design scalable analytical data models in BigQuery, AlloyDB PostgreSQL, and Snowflake; optimize SQL-based feature engineering, data
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