Data Scientist

4 weeks ago


San Jose, California, United States Western Digital Full time

Job Summary

We are seeking a highly skilled PhD Data Scientist to join our team at Western Digital. As a key member of our Analytics organization, you will be responsible for developing cutting-edge analytics solutions that drive significant impact on revenue, profitability, and shareholder value.

Key Responsibilities

  • Probabilistic Demand Forecasting : Develop probabilistic models that provide a range of possible demand outcomes with associated probabilities. Update demand forecasts dynamically as new information becomes available, using Bayesian principles to incorporate uncertainty in a structured way.
  • Demand vs. Supply Scenario Planning : Develop multiple scenarios based on different assumptions about future market conditions, demand trends, and external factors (e.g., macro-economic indicators, geo-political events).
  • Simulations & Quantitative Risk Management : Use Monte Carlo simulations and other probabilistic models to quantify & minimize the risk of different demand scenarios on inventory levels, production schedules, and profitability.
  • Financial Forecasting : Utilize financial econometrics to build models that support financial forecasting, including sales and revenue projections.
  • Pricing Optimization : Apply advanced analytics and optimization techniques to pricing strategies, including price gap analysis and pricing optimization.
  • Data Analysis : Acquire, cleanse, and transform large and complex datasets and analyze to extract actionable insights and support scenario planning & risk assessment models.
  • Collaboration with Cross-Functional Teams : Work closely with Product Marketing, Supply Chain, Sales, and Finance teams to identify business challenges and develop data-driven solutions.
  • Continuous Learning & Innovation : Stay up-to-date with the latest trends and technologies in econometrics, advanced statistics, game theory, and data science. Contribute to the continuous improvement of processes, tools, and methodologies.

Requirements

  • PhD in a field such as Economics & Data Science, Advanced Statistics, Applied Mathematics, or a related discipline.
  • Research experience in solving complex forecasting, risk management and cost or profit optimization problems.
  • Deep expertise in advanced statistical methods (e.g., Causal inference and Bayesian statistics), mathematical optimization, scenario planning, and simulations (e.g., Monte Carlo Simulations).
  • Ability to handle large and complex datasets, with proficiency in SQL, Hadoop, Spark, and NoSQL databases.
  • Proficiency in programming languages such as Python, R, or similar for data analysis and model development.
  • Prior experience or aptitude to learn Machine Learning, Deep Learning, and Generative AI techniques.
  • Ability to quickly learn and apply new tools and technologies, particularly in data visualization (e.g., Power BI, Spotfire) and cloud platforms (e.g., Oracle Cloud, AWS, GCP).
  • Strong interpersonal and communication skills with the ability to work effectively with cross-functional teams and present complex data-driven insights to non-technical stakeholders.
  • Critical thinking and an appetite to solve complex real-world problems.

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