Machine Learning Engineer II

About DAT

DAT is an award-winning employer of choice and a next-generation SaaS technology company that has been at the leading edge of innovation in transportation supply chain logistics for 45 years. We continue to transform the industry year over year, by deploying a suite of software solutions to millions of customers every day - customers who depend on DAT for the most relevant data and most accurate insights to help them make smarter business decisions and run their companies more profitably. We operate the largest marketplace of its kind in North America, with 400 million freights posted in 2022, and a database of $150 billion of annual global shipment market transaction data. Our headquarters are in Denver, CO, with additional offices in Missouri, Oregon, and Bangalore, India. For additional information, see www.DAT.com/company.

The Opportunity:

The Data Science team at DAT Freight & Analytics plays a central role building models, algorithms and tools to deliver insights to our customers, helping them streamline, strengthen, and grow their businesses. Our team's products run the gamut of data science topics, from time series forecasting, economic modeling, classification, and recommenders and now making our foray into leveraging Advanced AI capabilities like LLMs to build innovative solutions in supply chain and logistics.

As part of the Data Science team, you will help us move prototypes into production, support all existing ML and statistics products, grow our ML Operations tool set, integrate DS products with the rest of engineering and engage in research discussions and planning. As an Associate MLE, you get to contribute to the wide variety of machine learning projects that are directly influencing business decisions enabling revenue growth.

Responsibilities:

• Supporting the data science family of teams in moving prototype models into production.
• Developing sound operations tools for training, release, and rollback of production models.
• Developing model monitoring systems to ensure long-term model health and efficacy.
• Ownership of production models, ensuring they are properly updated and monitored for efficiency, accuracy, and costs.
• Creating batch processing systems and APIs to deploy and operationalize machine learning models in production environments.
• Working with DAT engineering teams to ensure seamless integrations between DS and the rest of DAT's engineering products.
• Refactoring older data science codebases to bring them up to date with current tools and processes.
• Supporting data science researchers as a peer, offering both scientific and technical input and feedback.
• Develop and maintain documentations of processes and standard operating procedures for Data science products.
• Work in Agile mode for delivering the outcomes of our Data science projects.

Required Skills/Experience:

• BS or higher degree in Mathematics, Statistics, Physics, Economics, Computer Science or other STEM disciplines.
• 1 - 2 years of experience as a data scientist, ML engineer, software engineer with ML experience or similar experience.
• Experience in Python, SQL, Git, GitHub.
• Using and/or maintaining CI/CD tools like Jenkins, Codefresh, Github Actions or similar.
• Experience with Docker, Kubernetes, or other containerization technologies.
• Experience working with Cloud technologies and services like AWS, Azure or similar.
• Have experience working with Infrastructure-as-Code tools like Terraform.
• Working experience with Snowflake.
• Familiarity with Project management platforms like JIRA, Confluence or similar.

Nice to Have:

• Post graduate degree in Mathematics or Computer science or other equivalent fields.
• Industry or academic experience in transportation logistics and supply chain.
• Building cloud-based data transformation pipelines (ETL).
• SQL, especially with Snowflake.
• Working knowledge of orchestration frameworks like Airflow.
• Demonstrated experience in owning an engineering module end to end in the past.
• Good understanding of Machine learning algorithms mathematically.

DAT embraces the value of a diverse workforce, and believes it is a core strength of our company that we encourage those values in every DAT employee, at every level of our organization, regardless of tenure or rank. We provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information. 41 CFR 60-1.35(c)

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