Senior Data Scientist (AI/ML)

Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today’s needs and tomorrow’s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we’re living in and that we have the power to shape.

Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry-leading portfolio of products that are recognized globally for innovation, performance and quality.

Sandisk has two facilities recognized by the World Economic Forum as part of the Global Lighthouse Network for advanced 4IR innovations. These facilities were also recognized as Sustainability Lighthouses for breakthroughs in efficient operations. With our global reach, we ensure the global supply chain has access to the Flash memory it needs to keep our world moving forward.

We're looking for a skilled Data Scientist 3 to join our analytics team in South Seberang Perai District, Malaysia. In this role, you will develop and implement data science solutions to address complex business problems, driving innovation through advanced analytics. The ideal candidate will be detail-oriented, analytical, and organized—bringing both technical expertise and collaborative problem-solving skills to deliver data-driven solutions.

Responsibilities

Design, develop, and implement machine learning models and statistical analyses to address complex business problems; Build and optimize data pipelines and ETL processes to ensure efficient data flow and quality across the organization; Collaborate with cross-functional teams including engineering, product, and business stakeholders to translate requirements into analytical solutions; Conduct exploratory data analysis and present actionable insights and recommendations to stakeholders; Contribute to establishing and maintaining data quality standards, implementing validation frameworks and monitoring systems; Stay current with emerging data science technologies, methodologies, and industry trends, evaluating their applicability to organizational needs; Support end-to-end project delivery, ensuring timely completion and alignment with business objectives

Requirements

Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.; 3+ years of professional experience in data science, machine learning, advanced analytics, or a related role.; Strong expertise in machine learning algorithms, statistical modeling, and predictive analytics.; Advanced proficiency in Python and/or R for data analysis, statistical computing, and model development.; Proficiency in SQL and experience working with relational database management systems.; Exceptional analytical and problem-solving skills with the ability to work effectively with large and complex datasets.; Strong communication and presentation skills, with the ability to translate complex technical findings for non-technical stakeholders.; Programming: Python, R; Databases & Querying: SQL, Relational Databases; Machine Learning: Predictive Modeling, Statistical Analysis, Machine Learning Algorithms; Big Data: Apache Spark, Hadoop; Visualization & Reporting: Tableau, Power BI; Development Tools: Git, Version Control, Collaborative Development Practices; Analytics: Data Exploration, Feature Engineering, Model Evaluation, Problem Solving; Communication: Data Storytelling, Technical Presentation, Stakeholder Engagement

Nice to have

Experience with big data technologies such as Apache Spark, Hadoop, or similar distributed computing frameworks.; Hands-on experience with data visualization and business intelligence tools such as Tableau, Power BI, or equivalent platforms.; Experience using version control systems (Git) and collaborative software development practices.; Experience deploying, monitoring, or maintaining machine learning models in production environments.