Charger logistics Inc. is a world- class asset-based carrier with locations across North America. With over 20 years of experience providing the best logistics solutions, Charger logistics has transformed into a world-class transport provider and continue to grow.

Charger logistics invests time and support into its employees to provide them with the room to learn and grow their expertise and work their way up. We are entrepreneurial-minded organization that welcomes and support individual idea and strategies.
Responsibilities:

• Understand business processes and translate analytical needs into scalable data and ML solutions using GCP.
• Collect and process structured and unstructured data from multiple internal and external sources to support model development.
• Perform exploratory data analysis (EDA) to uncover trends, anomalies, and root causes behind business outcomes.
• Develop and deploy advanced analytics models (ML/AI) using GCP services (BigQuery ML, Vertex AI, Dataflow, etc.).
• Build and automate end-to-end data pipelines for analytics and machine learning using GCP services like: BigQuery, Dataflow, Dataproc, Vertex AI, Cloud Functions, Pub/Sub, Cloud Composer (Airflow)
• Partner with software engineering teams to implement real-time data pipelines and APIs for model integration.
• Drive scalable and reproducible experimentation, validation, and deployment of ML models.
• Leverage tools like Python, SQL, and GCP-native tools for data wrangling, modeling, and deployment.
• Build dashboards and visualizations to present actionable insights to business stakeholders.
• Contribute to the development and implementation of data governance and MLOps best practices.

Requirements

• University degree or equivalent in data analytics, statistics, math, or computer science, with a minimum of 5 years relevant experience.
• Google Cloud Professional Data Engineer or Professional Machine Learning Engineer certification.
• Minimum of 3 years of hands-on Snowflake Practitioner experience in a Data Engineering role.
• Must be Snowflake Certified or should have experience in Snowflake. The SnowPro® Advanced: Data Scientist Certification is preferred.
• Experience with Azure, Databricks and AWS Services.
• Excellent knowledge of Python, Matillion and SQL, Pandas, ML, LLM.
• Experience on Azure ML Studio is Preferred.
• Good to have experience in Airflow and Matillion Studio.
• Good experience with Anomaly algorithms is an asset.
• Experience in big data processing and the development of Python and SQL for large amounts of data.
• Considerable experience with unit and integration testing.
• Excellent analytical, storytelling, and problem-solving skills.
• Ability to translate/communicate analytics recommendations to both technical and nontechnical team members.
• Strong understanding of quantitative (univariate and multivariate) analysis techniques.
• Experience with predictive modelling and machine learning.
• Strong experience with statistical analytical techniques, data mining, machine learning, and predictive models using Python, R , PySpark, Matillion, PyTorch, Numpy, Scikit-learn or similar tools.
• Experience using scripting language for collecting, organizing and manipulating data.
• Ability to work with data with significant ambiguity, develop creative approaches to analytical problems, and interpret data and results from a business/industry perspective.

Benefits

• Health Benefits
• Career Growth
• High Competitive Salary