Senior Engineer, Data Scientist

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We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities.

Samsung Semiconductor is hiring for a Senior Engineer, Data Scientist for the Customer Quality & Reliability (Q&R) team that is accountable to identify any major product quality and reliability issues as early as possible and help resolve them as swiftly as possible. You will be part of an incubation team within this organization working on in-field telemetry intended to transform the Customer Quality Experience for Samsung memory products. Fault Management is the future of quality to minimize system downtime within AI/ML hardware deployments based on customer field memory quality monitoring. We analyze trends and patterns from enormous memory fleet telemetry to bucketize failures and perform virtual root-cause analysis. Telemetry analysis helps us design solutions to proactively avoid system downtime. We conduct research and develop both in-house and collaboratively in the industry with the opportunity to publish our findings through whitepapers and conferences. We are looking for innovative and passionate thinkers who can work in a start-up environment and are excited to shape the future of data centers around the world. Join us in our mission!

What You’ll Do

• Performs complicated statistical and data -mining analysis, using statistical tools like Python, SQL, R and design of data acquisition systems, data structure and database design.
• Interfaces with internal customers for requirements analysis and special requests and schedules; derives insights and works with business units to determine actions and KPI for those actions
• Develop difficult analytical models, algorithms and automated processes, applying ML or data science techniques, to cleanse, integrate and evaluate large datasets.
• Build live reports to support large scale data visualization using Tableau, Power Bi etc.
• Interacts with product and service teams to identify questions and issues for data analysis and experiments; Supports the timely development of products for monitoring and evaluating quality and reliability of memory products.
• Work on data science research projects at the intersection of memory RAS & AI e.g., ML based customer failure rate projection model (with variable factors)
• Communicates insights and findings from analysis and experiments to product, service and business management.
• Stay up to date on latest industry trends in the hardware fault management space. Read technical papers, blogs, conference talks as well as publish whitepapers in conferences.
• Drive alignment with multiple stakeholders/teams within US and Korea.
• Drive communication and interaction with external customers regarding project goals and solution.

Location: Daily onsite presence at our San Jose office (2 days working from home in a month)

What You Bring

• Bachelor’s degree with 4+ years of relevant industry experience, or Master’s with 2+ years in Computer Science, Data Analytics, Electrical Engineering or related technical field preferred.
• 2+ years of Experience in application of ML (Machine Learning) in support of product quality analysis.
• Expertise in data mining, ML codebases, ML task development or automation, modeling, forecasting using statistics, analyzing trends and patterns, GUI design and deployment.
• Preferred experience within Semiconductor industry, knowledge of computer architecture fundamentals.
• Ability to collaborate with cross functional teams and have excellent communications skills.
• Innovative and creative, you proactively explore new ideas and adapt quickly to change.
• Have key achievements as a data science professional and initiatives that have transformed business.
• You’re inclusive, adapting your style to the situation and diverse global norms of our people.
• An avid learner, you approach challenges with curiosity and resilience, seeking data to help build understanding.
• You’re collaborativ