Data Scientist

At SAP, more than 78,000 of us flourish in an environment that encourages open, free expression of ideas. You'll work alongside creative thinkers who turn big ideas into reality for our customers. And with innovative job training, mentors to help you grow, and flexibility to balance work and personal life, you get more out of your career, too.

We are looking for a Data Scientist to be part of our Business Network team and help draw insights from one of the biggest B2B data stores in the world. A key trait to be successful in this role is to have a love for data and utilize it to solve critical problems and deliver end user value. You will create predictive models, extract insights from data, find patterns in payments and buying data, and use your analytical skills to take our business applications to the next level.

* Work with other data scientists, developers and cross functionally with product managers and other engineering teams to deliver predictive models from concept to product * Model Building Cycle – pull, cleanse, and validate data for analysis and modeling. * Create and implement predictive models for various business process like payment risk, relationship discovery, categorization (unsupervised learning), catalog optimization, etc. * Work with software engineers to put predictive models in production * Determine the tracking necessary to enable analytics of our products and features by working closely with product and engineering partners

* 2-4 years of experience * Strong understanding of applied statistical concepts such as regression, time series analysis, machine learning (supervised & unsupervised learning such as segmentation, classification and clustering) * Hands-on experience building models and machine learning algorithms * Experience coding in Java, C, C++, Scala or Python a plus * Knowledge of or experience working with big data (e.g., Hadoop) a plus * Be an iterative and quick thinker – you deliver preliminary results fast and then iterate over time M.S. or Ph.D. in Statistics, Mathematics, Economics, Computer Science (data mining or machine learning focus), or another quantitative scientific field.