ESSENTIAL DUTIES AND RESPONSIBILITIES:
As a Data Scientist, you will be working on Digital Innovation projects leveraging 4IR and cutting-edge technologies. You will be collaborating with Data Science Team to design and build analytics tools/models/analytics to accelerate digital technologies adoption and unlock business value from data insights. You are required to constantly learn new front-tier technology and creatively apply/deliver solutions to support Global Ops Strategy and goals.
- Work with a team of high-performing analytics, data science professionals, and cross-functional teams to understand business problem, identify business opportunities, optimize business performance and/or improve KPIs
- 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, machine learning, deep learning, NLP, LLM, GenAI visualization etc. to discover insightful patterns.
- Develop/take an idea, access and prepare necessary data to create prototype machine learning models/algorithms, develop it to an application with intuitive user interface, integrate with any pre-existing systems, demonstrate successful use cases and wins.
- 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
- Provide technical guidance and mentorship to junior team members on solution design
REQUIRED:
- Bachelor's Degree or Master's Degree in related fields and research projects related to Analytics/Data Science with relevant industry or academia experience.
- Background in at least one programming language (eg. R, Python, Java, Scala/Spark)
- 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 in models’ deployment and E2E model management through docker image, container, MLOps.
- 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.
- Experience in solution architecture, its technology stacks, and components.
PREFERRED:
- Excellent knowledge of at least one of the following programming languages / frameworks: Python, R, Java, SQL, Scala
- Excellent knowledge of the 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 Deep Learning, NN, NLP, LLM, etc
- Knowledge of web front-end development: HTML/CSS, JavaScript (JQuery or Angular preferred)
- Knowledge of Hadoop, including Hive, Map Reduce, No/SQL, HBase, and Spark
- Familiar with collaborative solutions, model & code versioning (Github), solution packaging (Docker)
- Practical experience of cloud-based solutions is a strong plus.
- 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, frequentist and Bayesian inference, clustering, cross-validation, NN, NLP, LLM, and data visualization.
- Knowledge in web crawling, NLP, visualization, and dashboard creation
- Ability to solve problems and provide complex solutions with limited direction.
- Ability to deploy data science solutions in cloud analytics infrastructure and AWS
- Analytical mind and business acumen. Application understanding of machine-learning and operations research
- Proactive and collaborative effectively in a rapidly changing environment (VUCA), 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.
- Excellent communications and presentation skills, with the ability to synthesize, simplify and explain complex problems to different types of audiences, including executives.
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 [email protected] 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.
