Marketing Data Scientist & AI Professional

Responsibilities

Our Marketing, Communications & Corporate Social Responsibility (MCC) team is responsible for positioning IBM in the market. We define and optimize IBM’s brand, capture the market’s attention, and articulate our point of view for clients, partners, the media, and even other IBMers. As part of our team, you’ll be surrounded by bright minds and keen collaborators – always willing to help and be helped – as you apply passion to work that will compel our audience to choose IBM’s products and services.

As a Marketing Data Scientist & AI Professional, you’ll work collaboratively, as part of a team, on a project that addresses a strategic IBM Marketing business challenge. This role supports our Performance Intelligence team, which is responsible for building intelligence that powers and orchestrates performance across tactics and buyer groups.

As a member of the team, you may:

Develop scalable analytical solutions that provide data-driven and optimization insights

Work with large, complex data sets and extract knowledge or insights to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed

Conduct end-to-end analysis that includes industry research, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations

Communicate informed conclusions and recommendations across the organization's leadership structure

Required education
Master's Degree

Preferred education
Master's Degree

Required technical and professional expertise

3+ years of relevant data science work experience in complex data querying environments, working with complex data models using Advanced SQL/Python or other query and programming tools to process and analyze data.

Advanced knowledge and experience working with large data sets and applying data mining / predictive modeling techniques to extract meaningful insights.

Thought leadership in working on functional objectives and shaping a solution.

Ability to translate business requirements into technical solution.

Familiarity with Microservices architecture, DevOps, deployment processes, and cloud platforms AWS, Azure, IBM Cloud, or Google Cloud.


Preferred technical and professional experience

Graduate degree in a quantitative discipline (e.g., statistics, data science, computer science, behavioral science, applied mathematics, operations research) or another discipline involving experimental design and quantitative analysis of data is a plus.

Experience with statistical analysis such as linear models, multivariate analysis, clustering, time series, mixed model, and Bayesian methods.

Relevant work experience in marketing analytics and web analytics is a plus.