Scientist 1, Data Science
- Business Function: Data Science
- Work Location: KL COE Office--LOC_WDT_KL COE
- Job Type (exemption status): Exempt position - Please see related compensation & benefits details below
The 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.
As a Data Scientist, you will be working on Digital Innovation projects leveraging 4IR technologies. You will be collaborating with Data Science Team to design and build Big Data tools/models/analytics to unlock business value from data insights. You are required to constantly learn new front-tier technology and creatively apply/deliver solutions to manufacturing operations to meet goals.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Work with a global team of data scientists, data engineers, software engineers, process & product engineers, design engineers, etc collaboratively to develop new data science solutions that improve productivity and operations metrics.
- Leverage data mining techniques in mathematics, statistics, information technology, machine learning, deep learning, data engineering, visualization etc to discover insightful patterns.
- Work on projects and develop solutions that would be of high impact to various areas at all manufacturing.
- Develop/take an idea, access and prepare necessary data to create machine learning models, develop it to an application with intuitive user interface, integrate with any pre-existing systems, demonstrate successful use cases and wins.
- Working with various scientific data such as equipment sensor data and logs, image and various types of signals, manufacturing process, ERP/MES data etc to extract meaningful information for analytics.
- Design, model and prototype machine learning models and algorithms to solve specific Supply Chain, Manufacturing, Inventory Management & Distribution problems.
- Strong understanding of business strategy to develop a clear vision of data science
- The ability to develop, tune, and deploy predictive models that explain or predict business outcomes
- Prepare and deliver presentations with data visualizations and business conclusions
- Develop and code, software programs, algorithms, typically on very large datasets, from multiple sources, including IoT devices/sensors
- Interprets actionable insights from large data and metadata sources and communicates the findings to product, service, and business leaders for product improvement
- Bachelor's Degree or Master's Degree in related fields and research projects related to Analytics/Data Science with relevant industry or academia experience.
- Experience with SQL, Relational databases, Big Data platforms, AWS, etc.
- Experience in applied statistics and statistical modeling. Practical experience in the application of ML and AI algorithms.
- Experience with Hadoop or other MapReduce paradigms, and associated languages such as Hive, Presto, etc.
- Experience working with structured, semi-structured, and unstructured data sources
- Full stack development experience is preferred
- Knowledge of Hadoop Environment, including Hive, Map Reduce, No/SQL, HBase, and Spark
- Excellent knowledge of at least one of the following programming languages / frameworks: Python, R, Java, Matlab, SQL, Scala
- Familiar with collaborative solutions, model & code versioning (Github), solution packaging (Docker)
- Practical experience of cloud-based solutions is a strong plus.
- Knowledge of Software Engineering standards and best practices is a strong plus
- Knowledge of the AI/ML Model Lifecycle Management and tools including EDA, Modelling, Integration/Deployment, Data/Model drift detection, Model retraining, etc.
- Up-to-date knowledge and skills in recent Machine Learning tools and techniques such as NN, NLP, Deep Learning, etc
- Passion for Innovation, collaboration with the eco-system, and creating value to the organization
- Aptitude to interact with functional or business stakeholders who are not familiar with ML Engineering considerations.
- Strong communication, analytical and creative problem-solving skills
- Strategically focused, impact-oriented, highly organized, and adaptable.
- Strong knowledge and experience with R, Python, or other statistical software
- Familiarity with core techniques in statistical and machine learning e.g. regularized regression, time series analysis, decision trees, boosting algorithms, neural networks, frequentist and Bayesian inference, power calculation, and experimental design, clustering, collaborative filtering, NLP, cross-validation and bootstrapping, and data visualization
- Strong interpersonal skills and maintain positive relationships with colleagues
- Proactive and collaborative effectively in a rapidly changing environment
- Solid grasp of statistics and probability
- Ability to solve problems and provide complex solutions with limited direction
- Analytical mind and business acumen. Application understanding of machine-learning and operations research
- Experience with manipulating massive-scale structured and unstructured data.
- Excellent communications and presentation skills, with the ability to synthesize, simplify and explain complex problems to different types of audiences, including executives. A great team player.
- Results-oriented, with growth and imaginative mindset and strong dedication and passion to identify and implement improvement opportunities. Strong drive for results.
- Proven track record to perform in an environment characterized by volatility, uncertainty, complexity, and ambiguity (VUCA)
- Ability to execute requests with strong attention to detail and strong time-management skills
- Knowledge in web crawling, natural language processing, visualization, and dashboard creation
- Ability to deploy data science solutions in cloud analytics infrastructure and AWS
- Excellent written and verbal English-language communication and presentation skills
Because Western Digital thrives on the power of diversity and is committed to an inclusive environment where every individual can thrive through a sense of belonging, respect, and contribution, we are committed to giving every qualified applicant and employee an equal opportunity. Western Digital does not discriminate against any applicant or employee based on their protected class status and complies with all federal and state laws against discrimination, harassment, and retaliation, as well as the laws and regulations set forth in the "Equal Employment Opportunity is the Law" poster.