Manager, Advanced Technologies - Data Science & Equipment Intelligence (all genders)
Lead and develop the Advanced Technologies Team, driving innovation in Data Science, Artificial Intelligence, Machine Learning, and Equipmen
Lead and develop the Advanced Technologies Team, driving innovation in Data Science, Artificial Intelligence, Machine Learning, and Equipmen
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Warum dieser Job gelistet ist
KI ist Gegenstand der Rolle (Kernbegriffe in Titel/Anforderungen). Prüfverfahren ansehen
Lead and develop the Advanced Technologies Team, driving innovation in Data Science, Artificial Intelligence, Machine Learning, and Equipment Intelligence including Vision System for semiconductor spin clean tools. - Define and execute the team s strategic roadmap, aligning advanced analytics and intelligent equipment solutions with business objectives, product strategy, and Industry 4.0 initiatives. - Oversee the development, deployment, and lifecycle management of machine learning models, predictive maintenance solutions, and equipment intelligence capabilities to improve performance, reliability, and customer value. - Lead cross-functional collaboration with engineering, product management, process engineering, and key account technology teams to identify strategic opportunities and accelerate innovation. - Communicate technical strategies, business value, and program progress to senior leadership and key stakeholders. - Manage team performance, workforce planning and talent development to build and retain a high-performing organization.
Master s degree or Ph.D. in Data Science, Computer Science, Statistics, Engineering, Applied Mathematics, or a related technical discipline. - 8+ years of experience in Data Science, Machine Learning, AI, Analytics, Software Engineering, or Equipment Intelligence, including experience delivering production-grade solutions. - Previous experience leading technical teams, programs, or innovation initiatives. - Strong understanding of machine learning, data engineering, big data architectures, predictive analytics, and intelligent systems. - Strong stakeholder management, project management, and organizational leadership skills. - Excellent communication and presentation skills. Preferred Qualifications - Experience managing data science teams within semiconductor equipment development. - Advanced knowledge of Python, statistical modelling, machine learning, and artificial intelligence. - Advanced knowledge in optical imaging and computer vision. What We re Offering This position is subject to the Austrian Collective Bargaining Agreement for Employees in the Metal Technology Industry in occupation group H.
A higher payment is negotiable depending on education, expertise and skills. The monthly salary is paid 14 times per year. Please follow the link below in the Employment in Austria section for further information.
Villach - a great place to live and work Follow the link and you will find on the spot the most important information about living, working and studying in and around Villach/Austria Our commitment We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results. Lam Research (Lam or the Company) is an equal opportunity employer.
Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company s intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.
Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.
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