Data Science Manager

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.

Job Application Deadline: 11/29/2024

The Opportunity

DAT is looking for a Data Science Manager to join our Data Science and Machine Learning teams, working hybrid in Denver, Colorado; Beaverton, Oregon; or remote Seattle, Washington

Candidate profile

At DAT Freight and Analytics, we build machine learning and analytical tools that power our products across all product lines. Our Data Science team collaborates closely with engineering, product management, and business intelligence teams to solve complex problems, including forecasting, recommendation systems, search, anomaly detection, historical benchmarking, and beyond. Our work leads directly to new products, enhancements to existing products, and internal tools like decision support and advanced business intelligence solutions.

The Data Science Manager is responsible for overseeing both the data science research and the machine learning engineering team to ensure the seamless integration of research outputs into production. This role bridges the gap between innovative research and scalable machine learning systems, guiding the direction, execution, and quality of all data science initiatives. The manager will focus on organizing research and engineering tasks, facilitating effective collaboration, and ensuring that machine learning models are built, tested, and maintained for production use.

What You’ll Do

• Strategic Leadership: Lead both the data science research and engineering teams, ensuring alignment with business goals, product roadmaps, and the company’s vision. Manage the entire lifecycle from research prototypes to production-ready machine learning products.
• Model Management: Ensure the reliable training, evaluation, and deployment of machine learning models, and tracking performance over time. Oversee model retraining, evaluation against new data, and deployment as microservice APIs for consumption across internal teams.
• Engineering Infrastructure: Manage the design and maintenance of ML infrastructure, including pipelines that handle large overnight batch processing jobs, cloud storage, and databases. Oversee the development and maintenance of shared code libraries that support both research and engineering teams.
• Cross-Team Collaboration: Coordinate with product management, engineering, and business intelligence teams to translate business problems into analytical use cases. Align research with business needs and ensure effective communication of research findings to drive product innovation.
• Project Management: Organize the day-to-day tasks of both research and engineering teams, update timeline estimates regularly, and communicate concise project updates to senior and executive leadership. Manage project risks, timelines, and expectations effectively.
• Quality Assurance: Take ownership of the quality of all ML products, ensuring that rigorous testing, evaluation, and monitoring are in place for all systems and models. Implement best practices in both research rigor and engineering robustness to maintain high standards.
• On-Call Management: Organize the team’s on-call schedule and foster a culture of collaboration and balance. Ensure new team members are trained to share the responsibilities with experienced engineers to prevent burnout and encourage team growth.
• Tooling & Innovation: Continuously explore and recommend new tools, technologies, and methods to enhance the efficiency and capabilities of both the research and engineering teams. Lead initiatives to design cloud-native ML systems that power DAT products.
• Mentorship & Development: Mentor team members across both data science research and engineering disciplines. Provide educational and professional development opportunities to foster growth in research, engineering best practices, applications of machine learning to business needs, and professional communication.

The Skills and Experience You’ll Bring

• Minimum 6 years of related experience with a Bachelor’s degree; or 3 or more years experience with an advanced degree, or equivalent work experience.
• At least 1 year of management experience in data science, data engineering, or an engineering-focused research field using related tools and platforms; or at least 3 years of informal leadership experience such as team lead, research lead, or principal scientist.
• Proven experience delivering machine learning models and products from research to production, which are relied on by engineering and business teams.
• Strong knowledge of machine learning, forecasting, and statistical techniques, with the ability to lead teams in applying these techniques effectively.
• Professional Python developer with proficiency in mentoring others in Python best practices for data science and engineering tasks.
• Strong experience in cloud-based data science tools and platforms (AWS preferred) to lead the team in designing scalable ML systems.
• Experience with Infrastructure-as-Code tools, especially Terraform, for cloud resource management.
• Proven ability to manage the implementation and scaling of machine learning models in production environments, from model development to deployment.

Why DAT?
DAT is an award winning employer of choice.

For starters, we have a hybrid work environment, but we also know what makes a great workplace. We have a time-tested and resolute set of operating values predicated on integrity, mutual respect, open communication, and executing with excellence. These values inform our strategic vision as much as any one of our products does. We’ve been an employer of choice in the Portland metropolitan area for four decades, and within one year of opening our Denver office, DAT was #26 on Built In Colorado’s 100 Best Places to Work In Colorado.

• Medical, Dental, Vision, Life, and AD&D insurance
• Parental Leave
• Up to 20 days of paid time off starting in year one
• An additional 10 holidays of paid time off per calendar year
• 401k matching (immediately vested)
• Employee Stock Purchase Plan
• Short- and Long-term disability sick leave
• Flexible Spending Accounts
• Health Savings Accounts
• Tuition Reimbursement Program
• Employee Assistance Program
• Additional programs - Employee Referral, Internal Recognition, and Wellness
• Free TriMet transit pass (Beaverton Office)
• Competitive salary and benefits package
• Work on impactful projects in a cutting-edge environment
• Collaborative and supportive team culture
• Opportunity to make a real difference in the trucking industry
• Employee Resource Groups

This position is not eligible for Visa sponsorship.

For Colorado-based candidates, in compliance with Colorado's Equal Pay for Equal Work Act, the minimum salary for this role is $150,000.00 + benefits. The maximum compensation for this role can vary significantly depending on your job-related skills and experience. DAT considers factors such as scope and responsibilities of the position, candidate's work experience, education and training, core skills, internal equity, and market and business elements when extending an offer.

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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