Machine Learning Engineer

Charger Logistics is a world class asset-based carrier. We specialize in delivering assets, on time and on budget. With the diverse fleet of equipment, we can handle a range of freight, including dedicated loads, specialized hauls, temperature-controlled goods and HAZMAT cargo.

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. We are currently expanding and looking to add a motivated individual to our team based out of our Brampton office.

Responsibilities:

• Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.
• Effectively communicate the analytics approach and how it will meet and address objectives to business partners.
• Advocate and educate on the value of data-driven decision making; focus on the “how and why” of solutioning.
• Lead analytic approaches; integrate solutions collaboratively into applications and tools with data engineers, business leads, analysts and developers.
• Create repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products.
• Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources.
• Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.
• Collaborate, coach, and learn with a growing team of experienced Data Scientists.
• Stay connected with external sources of ideas through conferences and community engagements

Requirements

• Bachelors Degree in Data Science, Computer Science, or related field.
• 4+ years of Data Science and Machine Learning experience required.
• Experience working with AWS tools like Sage maker is a plus.
• Proficiency in Python or R. Ability to write complex SQL queries.
• Proficiency with Machine Learning concepts and modeling techniques to solve problems such as clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets.
• Ability to implement ML best practices for the entire Data Science lifecycle.
• Experience with microservices and deployment of ML models.
• Experience on Cloud Data Warehouses (Snowflake Data Cloud, Google BigQuery, DataBricks Lakehouse, Azure Synapse).
• Artificial Intelligence / Machine Learning (Amazon Sagemaker, Azure ML Studio)
  Streaming Data Ingestion and Analytics (Amazon Kinesis, Apache Kafka)
• Ability to apply various analytical models to business use cases (NLP, Supervised, Un-Supervised, Neural Nets, etc.).
• Exceptional communication and collaboration skills to understand business partner needs and deliver solutions
• Bias for action, with the ability to deliver outstanding results through task prioritization and time management.

Benefits

• Competitive Salary
• Healthcare Benefit Package
• Career Growth