Principal Data Scientist

Description

We are seeking a highly motivated Senior Data Scientist to join our team and drive data-driven decision making across engineering, operations, and business functions. In this role, you will leverage advanced analytics, machine learning, statistical modeling, and large-scale data processing to transform complex datasets into actionable insights that improve products, processes, and business outcomes.

The ideal candidate is passionate about solving challenging problems, working with diverse data sources, and partnering with cross-functional stakeholders to deliver innovative analytical solutions. You will play a key role in designing and implementing scalable data science solutions, developing predictive models, and communicating insights that influence strategic and operational decisions.

Responsibilities

Lead end-to-end data science initiatives from problem definition through deployment, adoption, and value measurement. Develop machine learning, statistical, optimization, and AI solutions for complex engineering and business challenges. Analyze large-scale structured and unstructured data to generate actionable insights and recommendations. Design experiments, predictive models, forecasting systems, and anomaly-detection solutions. Build scalable data pipelines, automated workflows, analytical tools, and reusable data products. Create dashboards and visualizations that enable timely, data-driven decisions. Communicate technical findings and strategic recommendations to stakeholders and leadership.

Required Experience and Skills

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Operations Research, or a related field.
8+ years of experience in Data Science, Machine Learning, Analytics, or a related field.
Solid understanding of statistics, experimental design, hypothesis testing, and predictive modeling.
Proven track record of delivering data-driven solutions that generated measurable business impact.
Experience developing, validating, and deploying machine learning and statistical models, including Regression, Classification, Clustering, Forecasting, Anomaly Detection.
Experience working with large-scale structured and unstructured datasets.
Experience extracting, transforming, integrating, and analyzing data from multiple disparate sources.
Experience collaborating with cross-functional stakeholders to translate business requirements into analytical solutions.
Strong problem-solving and analytical skills.
Ability to influence decision-making through data insights and recommendations.
Excellent written, verbal, and presentation skills.

Desired Experience and Skills

Preference for Master's degree or PhD in Data Science, Computer Science, Statistics, Mathematics, Engineering, Operations Research, or a related field.
Experience leading end-to-end data science projects from problem definition through deployment and business adoption.
Experience defining analytics strategy and influencing organizational direction.
Experience mentoring junior data scientists, analysts, or engineers.
Experience in semiconductor, manufacturing, quality, supply chain, product, or engineering analytics.
Experience applying analytics to Yield improvement, Process optimization, Quality improvement, Forecasting, Capacity planning, Root-cause analysis, Anomaly detection.
Experience with cloud and big data platforms such as Azure, AWS, Databricks, or Spark.
Experience with Generative AI, Large Language Models (LLMs), and AI-assisted analytics solutions.
Expertise in deep learning frameworks such as TensorFlow or PyTorch.
Knowledge of optimization methods, causal inference, advanced forecasting techniques, or reinforcement learning.

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