Job Type (exemption status): Exempt position - Please see related compensation & benefits details below
Business Function: Data Management Engineering
Company DescriptionThe future. It's on you. You & Western Digital.
We've been storing the world's data for more than 50 years. Once, it was the most important thing we could do for data. Now we're helping the world capture, preserve, access and transform data in a way only we can.
The most game-changing companies, consumers, professionals, and governments come to us for the technologies and solutions they need to capture, preserve, access, and transform their data.
But we can't do it alone. Today's exceptional data challenges require your exceptional skills. It's You & Us. Together, we're the next big thing in data.
Western Digital data-centric solutions are found under the G-Technology, HGST, SanDisk, Tegile, Upthere, and WD brands.
Job DescriptionLead the development of innovative data science solutions to a variety of business problems.
Design and implement data analysis, machine learning, and artificial intelligence algorithms, such as Computer Vision, GenAI, etc.
Develop and maintain prototype systems for data analysis, visualization, and predictive analytics.
Collaborate with stakeholders across the organization to identify areas of opportunity for data science initiatives.
Monitor and evaluate results of data science projects to ensure successful outcomes.
Implement best practices for data engineering and data science processes.
Provide guidance and leadership to more junior engineers in the team.
Stay up-to-date on the latest trends in data science and share knowledge with the team.
QualificationsMaster's or Bachelor's Degree in Computer Science, Data Science, Computer Engineering, Information Technology, or similar field with at least 4-5 years of working experience.
Proficient in programming languages such as Python, with a strong understanding of relevant data science libraries and frameworks.
Excellent communication and leadership skills.
Proven ability to manage and mentor a diverse team.
Enthusiasm for exploring and implementing the latest advancements in data science.
Knowledge of the AI/ML lifecycle management and tools including EDA, Modelling, Integration/Deployment, Data/Model drift detection, Model retraining, etc.
Practical experience in the application of ML and Deep Learning algorithms.
Familiar with collaborative solutions, model & code versioning (GitHub), and solution packaging (Docker).#J-18808-Ljbffr