Principal Data Scientist - Sales and Marketing

Reposted Yesterday
2 Locations
In-Office
Senior level
Automotive • Internet of Things • Mobile • Semiconductor • Industrial
The Role
Lead AI-driven initiatives as the first dedicated Data Scientist for Sales and Marketing, develop machine learning models, optimize sales opportunities, and mentor junior data scientists.
Summary Generated by Built In
Principal Data Scientist

Do you enjoy working with cutting-edge technologies in Data, AI, and Machine Learning? Are you excited by the opportunity to make a transformational impact in a Fortune 500 enterprise? Our Global Sales and Marketing (GSM) business domain is seeking a results-oriented Senior Data Scientist to lead AI-driven initiatives. You will collaborate with internal enablement teams (e.g., Central Data Office, IT) to deliver impactful AI/ML/GenAI use cases across the ML lifecycle.

As the first dedicated Data Scientist in the Global Sales and Marketing domain, you will play a pivotal role in shaping our data and AI driven strategy. You will lead the development of AI/ML solutions that drive customer insights, optimize sales opportunities, and influence strategic decisions across the organization.

Key Responsibilities
  • Lead the development of AI/ML solutions that drive customer insights, optimize sales opportunities, and influence strategic decisions across the Global Sales and Marketing (GSM) domain.  Initial efforts will focus on advancing Customer 360 and Cross-Sell use cases.

  • Partner with Sales, Marketing, and Business Development teams to identify high-impact use cases and translate business needs into data science solutions.

  • Ability to set data science best practices and support adoption of use cases across the organization.

  • Design and develop machine learning models to predict customer behavior, identify sales opportunities, and generate actionable insights, using a variety of 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).

  • Perform large-scale experimentation to identify hidden relationships between variables, and build models to answer business questions

  • Design and conduct data analyses with the highest standard of scientific rigor; this includes study design, methodology, algorithms, and statistical modeling.

  • Define and track success metrics for AI/ML initiatives to measure business impact and model performance

  • In collaboration with the Central Data Office (CDO) and IT teams, build ML pipelines and workflows to efficiently manage solution needs throughout the ML lifecycle.

  • Work closely with our MLOps engineers to move prototypes into robust, scalable production systems using automated workflows.

  • Contribute to the development of a long-term data strategy for the GSM domain, including data acquisition, quality, and governance.

  • Champion responsible AI practices and contribute to the development of governance standards across the ML lifecycle

  • Mentor junior data scientists and contribute to building a high-performing data science culture within GSM.

Job RequirementsEducation
  • Minimum of a bachelor’s degree in a STEM-related field (Engineering, Computer Science, Physics, etc.), Econometrics, or other related quantitative discipline with a strong foundation in statistics and specialization in AI/ML.  Master’s or PhD preferred.

  • Ideal candidate will have experience in B2B sales or enterprise marketing analytics

  •  Must have at least 8 or more years of related industry experience as a data analyst, with at least 3 years supporting a sales and marketing team

Experience
  • Proven experience with developing and deploying AI/ML enabled solutions to a Sales and Marketing organization is a must.  Experience in the semiconductor industry is a strong plus.

  • Demonstrated ability to integrate and analyze external data sources (e.g., company websites, trade news, SEC Edgar filings)

  • 8+ years of experience delivering end-to-end data science solutions, including statistical analysis, data engineering, feature engineering, and model deployment. Proven ability to lead cross-functional projects and optimize models for performance and scalability.

  • Experienced in working within Agile frameworks, participating in sprint planning, daily standups, and retrospectives to iteratively build and deploy models.

  • Hands-on experience in software development best practices (CI/CD), version control, including release management, testing and documentation.

  • Experience designing and integrating APIs to connect data science workflows with enterprise platforms, including Salesforce; familiarity with Salesforce data models and REST API usage preferred.

  • Led or contributed to the implementation of AI governance frameworks, ensuring responsible AI use through model transparency, explainability, monitoring, and alignment with enterprise risk and compliance standards.

Skills
  • Proficient in Python, with hands-on experience using libraries such as pandas, numpy, scikit-learn, xgboost, lightgbm, statsmodels, prophet, spaCy, matplotlib, seaborn, plotly, scrapy, and lxml.

  • Deep understanding of supervised and unsupervised learning techniques, model evaluation, feature engineering, and statistical modeling. Familiarity with experiment tracking tools like MLflow.

  • At least 1 year experience with LLM-based generative AI frameworks and tooling, including orchestration libraries (e.g., LangChain, LlamaIndex), transformer model libraries (e.g., Hugging Face Transformers), and commercial model APIs (e.g., AWS Bedrock, etc.)

  • Experience deploying machine learning models using Databricks MLflow Model Serving (preferred) or via custom APIs using FastAPI or Flask. Skilled in building scalable ML pipelines using Airflow and/or Databricks Workflows for orchestration.

  • Strong understanding of CI/CD practices and version control using Git and GitLab.  Strong working knowledge of AWS services (e.g. S3, SageMaker, Lambda) and Databricks on AWS.

  • Skilled in extracting and analyzing unstructured data from external sources using NLP techniques and tools like transformers, spaCy, and nltk.

  • Excellent communication and stakeholder engagement skills. Ability to translate complex technical concepts into actionable business insights.

  • Strong understanding of ML observability and AI governance

Location
  • This position can be located in Austin, TX or Irvine, CA.  This is a hybrid position with 3D's in the office and two days working from home each week. It is not open to 100% remote

More information about NXP in the United States...

NXP is an Equal Opportunity/Affirmative Action Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, NXP will provide reasonable accommodations for otherwise qualified disabled individuals.

#LI-6692

Top Skills

Airflow
AWS
Databricks
Fastapi
Flask
Lightgbm
Lxml
Matplotlib
Numpy
Pandas
Plotly
Prophet
Python
Scikit-Learn
Scrapy
Seaborn
Spacy
Statsmodels
Xgboost
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The Company
HQ: Eindhoven
21,993 Employees
Year Founded: 2006

What We Do

NXP Semiconductors N.V. (NASDAQ: NXPI) enables a smarter, safer and more sustainable world through innovation. As a world leader in secure connectivity solutions for embedded applications, NXP is pushing boundaries in the automotive, industrial & IoT, mobile, and communication infrastructure markets. Built on more than 60 years of combined experience and expertise, the company has approximately 34,500 employees in more than 30 countries and posted revenue of $13.21 billion in 2022. Find out more at www.nxp.com.

Privacy Policy: https://www.nxp.com/company/about-nxp/privacy-policy-for-social-media-pages:PRIVACY-POLICY-SOCIAL-MEDIA

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