Senior Manager, Applied Science

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers.

Summary:

Responsible for leading advanced applied science initiatives that drive innovation, optimize business outcomes, and expand the capabilities of data-driven products and services. This role requires strategic oversight, technical excellence, and the ability to translate scientific advancements into real-world applications. It involves cross-functional collaboration, mentoring, and execution of complex machine learning and artificial intelligence solutions.

Duties & Responsibilities:

• Lead a team of applied scientists and machine learning engineers in developing and deploying advanced models and algorithms.
• Drive the technical vision, research agenda, and roadmap for applied science initiatives aligned with business priorities.
• Oversee experimentation, evaluation, and deployment of machine learning models into production environments.
• Collaborate with Product, Engineering, and Data teams to integrate models into scalable systems.
• Champion best practices in scientific rigor, experimentation, reproducibility, and responsible AI.
• Mentor team members and foster a high-performance culture grounded in innovation and continuous learning.
• Monitor project progress, remove blockers, and ensure delivery of high-impact outcomes on time and within scope.
• Represent the applied science function in executive and strategic planning discussions.

Qualifications:

• PhD or Master’s degree in Machine Learning, Computer Science, Statistics, or a related field.
• 12+ years of experience in applied science or machine learning roles, including at least 3 years in a management role.
• Proven experience building and deploying ML models in production systems.
• Deep understanding of supervised, unsupervised, and deep learning techniques.
• Strong coding skills in Python and proficiency with ML frameworks such as PyTorch or TensorFlow.
• Excellent communication, stakeholder management, and cross-functional leadership skills.
• Experience managing complex technical projects and delivering measurable business impact.