Data Scientist

Introduction
At IBM we believe technology shapes the world and we are a catalyst for that innovation and creativity. We are on the forefront of groundbreaking change – improving businesses society and the human condition. As a leader in Hybrid Cloud and AI we are leading the charge in a world-wide digital transformation.

Our Marketing Communications & Corporate Social Responsibility (MCC) team tells this story and 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.

When you join IBM you join a culture of openness collaboration and trust. You join a team of IBMers who are helping technology support a positive global transformation. So join us and experience a place where you can co-create your learning and opportunities. A place where teamwork and unique ideas are treasured. A place where you can bring innovation to life.

Your Role and Responsibilities
Our Experience Engine team is comprised of data experts and Demand drivers who own the planning execution and optimization of our brand to demand to sales experiences in order to convert our qualified pipeline into revenue growth. We believe data powers the insights companies use to transform the way we work. We are looking for a Data Scientist who enjoys analyzing data to push marketers to take action and improve campaign performance and who has proven experience finding actionable insights in large data sets that lead to measurable business results.
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Required Technical and Professional Expertise

• Data Extraction and Manipulation: Ensures sound data usage for meaningful result interpretation. Experience with discovery & extraction of various data types relevant to a project.
• Coding for Data Science: Ensures robust & reproducible implementation of algorithms and experiments. Deep experience with python libraries.
• Statistics Machine Learning and AI: Builds expertise in tools & techniques to evaluate trust and transparency. Masters use of data science platforms and tools

Preferred Technical and Professional Expertise

• Knowledge of data tools basic statistics machine learning advanced math data manipulation.
• A solid foundation typically in statistics modeling operations research computer science and applications and math.
• Strong business acumen coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge.
• Effective at deploying an analytics solution thereby realizing business value.