Data Scientist

Key Skills

Aartificial intelligence, Algorithms, Analytical and Problem solving, Apache Hadoop, Apache Hive, AWS, Big Data Technology, Data science techniques, Data Visualization, Deep Learning, Docker, Effective communication skills, Github, HBase, Java Programming, Machine learning techniques, MapReduce, MATLAB Programming, Natural Language Processing (NLP), NoSQL, Python Programming, R Programming, Scala Programming, SPARK Programming, SQL

Job Description

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.
• Work on projects and develop solutions that would be of high impact to various areas at all manufacturing.
• Analyze large-scale structured and unstructured data; develop deep-dive analysis and machine learning / AI models to drive business value and improve KPIs.
• Leverage data mining techniques in mathematics, statistics, information technology, machine learning, deep learning, visualization etc to discover insightful patterns.
• 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.
• Design model and prototype machine learning models and algorithms to solve specific Manufacturing problems.
• 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
• Prepare and deliver presentations with data visualizations and business conclusions

Qualifications

REQUIRED:

• Bachelor's Degree or Master's Degree in related fields and research projects related to Analytics/Data Science with relevant industry or academic 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.
• Background in at least one programming language (eg. R, Python, Java, Scala/Spark)
• 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. Familiarity with common data modeling approaches and good understanding of how to deal with various datatypes, larger data sets, and parallel computing problems.

PREFERED:

• Knowledge of Hadoop, 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), and solution packaging (Docker)
• Practical experience of cloud-based solutions is a strong plus.
• Excellent knowledge of AI/ML Model development, Lifecycle Management (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
• Aptitude to interact with functional or business stakeholders who are not familiar with ML Engineering considerations.
• Passion for Innovation, continue learning new techniques. Monitor the market for emerging technologies for adoption and work on proof of concepts then scale for full deployment.

SKILLS:

• 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, tree base models, boosting algorithms, neural networks, frequentist and Bayesian inference, power calculation, clustering, collaborative filtering, NLP, cross-validation and bootstrapping, and data visualization
• 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
• 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 a growth and imaginative mindset and strong dedication and passion to identify and implement improvement opportunities. Strong drive for results.
• Ability to deploy data science solutions in cloud analytics infrastructure and AWS

Additional Information

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.

Western Digital is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at jobs.accommodations@wdc.com to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.