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Senior Staff Data Scientist Tekion. Job Description. . Tekion is seeking a highly skilled and experienced Senior Staff Applied Science Engineer to contribute to the development of innovative machine learning (ML) and artificial intelligence (AI) solutions within the automotive industry. In this role, you will collaborate with cross-functional teams to design, build, and deploy data-driven solutions that enhance customer experiences and optimize business operations. You will play a key role in implementing and improving ML models, driving technical innovation, and supporting the overall data science strategy. This position requires strong technical expertise, problem-solving skills, and the ability to work effectively within a team.. . Roles and Responsibilities. . . Strategic Leadership: Lead and mentor cross-functional teams in the design and development of innovative ML/AI solutions aligned with business objectives and long-term product strategy.. . Advanced Model Development: Architect, build, and deploy advanced machine learning models to address complex automotive industry challenges, ensuring production-level quality and scalability.. . Data Strategy: Identify and integrate new data sources, develop sophisticated data pipelines, and implement innovative methodologies to enhance model performance and impact.. . End-to-End Solution Delivery: Oversee the full ML lifecycle, from problem definition and data exploration to deployment and monitoring of production systems.. . Performance Optimization: Define and track key performance metrics for offline and online evaluations, driving continuous improvements in model accuracy and system performance.. . Cross-Functional Collaboration: Partner with Product, Engineering, and Business teams to understand requirements, translate them into technical solutions, and ensure successful delivery.. . Thought Leadership: Stay ahead of industry trends and emerging technologies, influencing the strategic direction of Tekion’s data science initiatives.. . Innovation and Research: Drive research and experimentation in cutting-edge machine learning areas such as deep learning, reinforcement learning, and generative models to create differentiating solutions.. . Operational Excellence: Implement best practices for MLOps, model governance, and scalable deployment to ensure reliability and performance of ML solutions in production.. . Mentorship: Provide technical guidance and mentorship to junior and mid-level data scientists, fostering a culture of learning and innovation.. . . Skills and Experience. . . Education: Master’s or Ph.D. in Data Science, Machine Learning, Computer Science, Mathematics, or a related field.. . Experience: 10+ years of hands-on experience in Data Science and Machine Learning, with a proven track record of delivering impactful, production-grade solutions.. . Technical Expertise: Deep proficiency in Python (or similar languages), with strong experience in ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.. . Big Data Experience: Expertise in working with large-scale data processing frameworks (e.g., Spark, Hadoop) and streaming technologies (e.g., Kafka, SQS).. . Cloud & Infrastructure: Strong experience with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) for scalable ML deployment.. . Advanced ML Knowledge: In-depth knowledge of advanced ML techniques, including deep learning, recommendation systems, NLP, and computer vision.. . Problem-Solving: Exceptional problem-solving and analytical skills with a strong business acumen.. . Collaboration: Proven ability to work cross-functionally and influence decision-making at all levels of the organization.. . Communication: Excellent communication skills, capable of articulating complex concepts to both technical and non-technical stakeholders.. . . Preferred Skills. . . Expertise in Recommendation Systems and Natural Language Processing (NLP).. . Deep understanding of the automotive industry and related workflows.. . Experience building and scaling MLOps pipelines for continuous integration and deployment.. . Familiarity with model governance, compliance, and ethical AI practices.. . Active participation in the ML/AI research community or contributions to open-source projects.. . A proactive, innovative mindset with the ability to thrive in fast-paced, ambiguous environments..