Data Scientist

NXP Semiconductors Sales seeks an experienced and results-oriented Data Scientist to contribute to our AI-driven initiative, providing comprehensive Customer 360 insights to our Sales team. This role centers on developing and deploying AI/ML models and Generative AI Retrieval Augmented Generation (RAG) solutions, synthesizing information from diverse internal and external sources to empower our sales force. Experience with AWS AI/Generative AI tools as well as Salesforce Einstein is highly desired. This role requires a strong understanding of Generative AI and ML implementations for various sales scenarios, proficient programming skills, and excellent English communication. Semiconductor industry and Sales experience are highly valued.

Responsibilities:

• Collaborate with cross-functional teams (executives, sales, marketing, and Salesforce) to translate business needs into actionable data science solutions.
• Conduct exploratory data analysis (EDA) on complex data sources, including internal systems (e.g., Sales Order, Revenue Forecasts, Design Win Opportunities) and external sources (e.g., company websites, trade news, SEC Edgar filings).
• Design and develop machine learning models to predict customer behavior, identify sales opportunities, and generate actionable insights.
• Develop data pipelines and ETL processes for ingesting, cleaning, and transforming disparate data sources to build RAG instances and train ML models.
• Implement and support Generative AI prompt user interfaces, providing training and enablement to users.
• Deploy and maintain production-ready machine learning models, ideally leveraging AWS or Salesforce environments.
• Create visualizations and reports to effectively communicate insights and findings to stakeholders.
• Maintain awareness of advancements in AI, particularly within the Generative AI domain.
• Collaborate with the Salesforce team, the CDO (Chief Data Office), and IT data scientists and engineers to enhance AI capabilities.

Qualifications:

• Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, or a related quantitative or business field.
• Three or more years of demonstrated experience as a Data Scientist, with a proven track record of successful project implementations.
• Deep understanding of statistical modeling, machine learning algorithms, and data mining techniques.
• Proven ability to implement and optimize Generative AI solutions, including experience leveraging company internal and external data within Retrieval Augmented Generation (RAG) databases.
• Proficiency in Python and R, coupled with experience using machine learning libraries and frameworks such as scikit-learn, TensorFlow, and PyTorch.
• Expertise in data engineering, and working with large, complex datasets comprising structured, unstructured, and external web data.  Databricks experience is a plus.
• Proficiency with AWS cloud computing platforms.
• Demonstrated data visualization skills using tools such as Tableau or Power BI.
• Experience with Salesforce (including Einstein and Data Cloud) and ModelN is highly desirable.
• Experience within the semiconductor or high-tech industry, particularly in Sales, Marketing, or Supply Chain, is a strong plus.

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