Scientist 2, Data Science

At Western Digital, our vision is to power global innovation and push the boundaries of technology to make what you thought was once impossible, possible.

At our core, Western Digital is a company of problem solvers. People achieve extraordinary things given the right technology. For decades, we've been doing just that—our technology helped people put a man on the moon and capture the first-ever picture of a black hole.

We offer an expansive portfolio of technologies, HDDs, and platforms for business, creative professionals, and consumers alike under our Western Digital, WD, WD_BLACK, and SanDisk Professional brands.

We are a key partner to some of the largest and highest-growth organizations in the world. From enabling systems to make cities safer and more connected, to powering the data centers behind many of the world's biggest companies and hyperscale cloud providers, to meeting the massive and ever-growing data storage needs of the AI era, Western Digital is fueling a brighter, smarter future.

Today's exceptional challenges require your unique skills. Together, we can build the future of data storage.

Responsibilities related to data science and machine learning in a manufacturing context. Key tasks include collaborating with cross-functional teams to create impactful data solutions, analyzing large datasets to enhance business metrics, designing and implementing machine learning models, developing scalable computer vision solutions, and maintaining web applications for data initiatives. Additionally, it involves interpreting data insights, communicating findings to stakeholders, and delivering presentations with visualized data and business conclusions.

• Collaborate with cross-functional teams to develop high-impact data science solutions that improve productivity and operations metrics
• Analyze large-scale data and develop machine learning/AI models to drive business value and improve KPIs
• Design, prototype, and implement machine learning models and algorithms to solve specific Manufacturing problems
• Researching and developing scalable computer vision and machine learning solutions for complex problems
• Create and maintain web applications to support data science initiatives and facilitate data-driven decision making
• Interpret actionable insights from data and metadata sources, communicating findings to stakeholders for product improvement
• Prepare and deliver presentations with data visualizations and business conclusions

REQUIRED:

• Bachelor's degree inComputer Engineering, Software Engineering, Data Science, andRobotics & AI Engineering  with relevant industry or academic experience in data analytics
• Proficiency in SQL, Big Data platforms, and cloud services (e.g., AWS)
• Strong background in applied statistics, statistical modeling, and practical experience with ML and AI algorithms.
• Required: Python, Tensorflow framework, Computer Vision
• Familiar with collaborative solutions, model & code versioning (Github), and solution packaging (Docker)
• Strong communication, analytical, and problem-solving skills.

PREFERRED:

• Knowledge of AI/ML model development and lifecycle management.
• Experience with cloud-based solutions and collaborative tools (e.g., Github, Docker).
• Experience in Computer Vision and image processing techniques.
• Experience in web development.
• Familiarity with advanced machine learning techniques (e.g., neural networks, NLP, deep learning).
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Proactive approach to learning and implementing emerging technologies.

Western Digital thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.

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