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. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Job Description: 

Tekion is seeking a passionate and dynamic Senior Manager of Applied Science to lead a team of applied Scientists focused on building next-generation AI applications on the cloud. You will work closely with product, business, machine learning engineering, and customer success teams to align priorities, timelines, and deliverables. You will drive AI/ML development efforts and ensure customer engagements are supported with high-quality, scalable solutions that deliver measurable impact.

Key Responsibilities:  

Leadership and Team Management 

• Lead, mentor, and manage a team of applied scientists, including senior scientists and team leads. 

• Build and scale a high-performing team of 5-8 scientists; provide regular mentoring and establish clear career development paths. 

• Set and promote best practices for research, development, code quality, and technical excellence 
   

Customer Engagement & Deliverable Management 

• Collaborate with product and customer success teams to prioritize customer needs and align development timelines accordingly. 

• Integrate customer feedback into development cycles, adapting priorities as business needs evolve. 

• Act as the technical point of contact for customer engagements, setting clear expectations for deliverables and timelines. 

• Ensure high-quality, on-time delivery of customer-facing AI/ML products that meet or exceed expectations. 
   

Product Development & Strategy 

• Lead the execution of the R&D and product roadmap, aligning ML initiatives with business goals and customer priorities. 

• Drive product strategy in collaboration with product management, business development, and operations. 

• Provide architectural and technical leadership on key projects, ensuring robustness, scalability,and flexibility. 
   

Scalability & Best Practices 

• Foster a high-performing team through agile workflows, continuous improvement, and strong delivery processes. 

• Architect and implement scalable AI/ML solutions aligned with ASD's long-term vision, using cloud-native technologies and microservices. 

• Oversee the full ML lifecycle-including data collection, model training, validation, deployment, and monitoring-ensuring effective team collaboration and resource management. 

• Promote advanced techniques such as model compression, quantization, and distributed training. 

• Champion industry best practices in development to ensure code quality, performance, and scalability. 

• Stay current with advancements in ML and lead team engagement in the broader scientific community. 

• Collaborate with design, product, and engineering teams to deliver high-performance solutions in a fast-evolving environment. 
   

Required Qualifications 

• Bachelor’s, Master’s, or Ph.D. in Data Science, Mathematics, Operations Research, Applied 

• Mathematics, Computational Science, or related fields. 

• Strong foundation in probability, statistics, and scientific problem-solving. 

• 12+ years of hands-on experience in analytics, data science, and deep learning in business-critical environments. 

• 3+ years of experience managing teams of 5 or more, preferably in applied science or cross-functional settings.. 

• Proven track record of delivering high-impact, data-driven solutions to complex business problems. 

• Proficient in machine learning, deep learning, and explainable AI techniques, with the ability tocommunicate technical concepts to non-technical stakeholders. 

• Experience developing and deploying state-of-the-art ML models tailored to specific business needs. 

• Strong programming skills in Python and SQL; experience with feature engineering and deep learning pipelines. 

• Familiarity with deep learning frameworks such as TensorFlow, Keras, and PyTorch. 

• Experience with computer vision (e.g., OpenCV) and natural language processing (e.g., spaCy). 

• Skilled in the Design of Experiments for scientific testing and optimization. 

• Proficient in Git for version control and collaboration. 

• Working knowledge of cloud platforms such as AWS, GCP, and Azure. 

• Strong analytical thinking and structured problem-solving abilities. 

• Excellent communication and collaboration skills in cross-functional teams. 
   

Preferred Qualifications 

• Demonstrated leadership experience in mentoring junior engineers and managing cross-functional projects. 

• Proven innovation track record—solutions that delivered significant business impact or led to patents. 

• Self-motivated, proactive problem-solver with strong project ownership. 

• Domain knowledge or experience in recommendation systems, NLP, or computer vision. 

• Strong collaboration skills across multiple teams, with an ability to manage conflict and align priorities. 

 

Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics. 

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