Senior Marketing Data Scientist

The Global Marketing Engines and Experiences (E&E) team within Microsoft is responsible for delivering integrated marketing experiences for Microsoft by building, running, and innovating a globally scaled engine to deliver connected journeys that delight customers and create fans. The Marketing Analytics and Data Science team within E&E enables data-driven decision making by providing data products and insights to measure marketing’s performance and impact, understand the customer experience, and develop advanced models for marketing.

As a Senior Marketing Data Scientist in E&E, you will apply full-stack data mining, modeling, experimentation and statistical techniques to data from multiple sources to identify new patterns, detect analytical opportunities and build solutions that enable impactful data-driven decisions. You will contribute to the development and tracking of key performance indicators related to customer engagement and build complex analytical models that evaluate marketing campaign performance, business impact and highlight opportunities for future growth. We are seeking someone who is curious, comfortable with ambiguity, detail-oriented and able to use rigorous techniques to develop scalable, efficient, and effective advanced models and data products, at times taking a deep dive into data to tell a story. In addition, you will build on the successes of others, value cross team collaboration, and contribute to a diverse and inclusive workplace.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities

• Lead large, complex projects to deliver accurate, accessible, secure and repeatable data products aligned to business and organizational needs and priorities that enhance our ability to inform marketing efforts, increase effectiveness of our approaches and deliver measurable outcomes.
• Demonstrate leadership and subject matter expertise in business and data landscape, visualizations, experimentation, and analysis to effectively communicate and support data driven decision making.
• Design and implement repeatable and scalable statistical and ML based frameworks to identify changes in behavior, business performance and other outcomes to help us make predictions and recommendations, set forecasts, identify anomalous activities, and understand outcome trajectory.
• Partner with Data Services on technical requirements to ensure adherence to security and compliance guidelines and enable data availability, data quality and integrity for data science, analytics and wider business self-service usage.

Qualifications

Required Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• 4+ years of experience with data engineering and modeling tools applied to Petabyte-scale data sets (e.g. Azure Data Factory, Azure Synapse, Spark).
• 4+ years of scripting experience writing efficient, readable and extensible code.
• 4+ years of experience with Advanced fluency in tools for navigating and analyzing data (e.g. SQL, R, Python).
• 4+ years of experience implementing and applying AI/ML algorithms and frameworks, including causal inference, mixed effects models and time-series modeling.

Preferred Qualifications

• Experience with LLMs, prompt engineering, and Azure AI APIs
• Skilled in multi-agent frameworks like AutoGen, Semantic Kernel, and Langchain
• Knowledge of MLOps practices: containerization, infrastructure-as-code, monitoring
• Proficient in debugging, security, and data protection principles

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until June 13, 2025.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

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