SAP Concur- Data Scientist Job

Job Description

Requisition ID: 221076
Work Area: Software-Research
Expected Travel: 0 - 10%
Career Status: Professional
Employment Type: Regular Full Time

COMPANY DESCRIPTION

SAP started in 1972 as a team of five colleagues with a desire to do something new. Together, they changed enterprise software and reinvented how business was done. Today, as a market leader in enterprise application software, we remain true to our roots. That’s why we engineer solutions to fuel innovation, foster equality and spread opportunity for our employees and customers across borders and cultures.
SAP values the entrepreneurial spirit, fostering creativity and building lasting relationships with our employees. We know that a diverse and inclusive workforce keeps us competitive and provides opportunities for all. We believe that together we can transform industries, grow economics, lift up societies and sustain our environment. Because it’s the best-run businesses that make the world run better and improve people’s lives.

The SAP Concur Engineering team responsible for our end user facing properties (mobile and web) is looking for a curious and creative data scientist to use Machine Learning and related technologies, to help separate signal from noise in our operational data in order to focus engineering on issues that will have the greatest impact to our customers. This is a green field opportunity for the right candidate who can integrate into a team of architects, engineers, SRE’s, and product owners focused on understanding user behavior and failure patters. You will engage in all steps from idea, data exploration, model building, deployment, and refinement.

The Role

• Have passion for data analysis and Machine Learning!
• Work with people throughout the company to understand the business and where we can best improve it.
• Build the necessary data features needed to support modeling.
• Use your data science background to build Machine Learning models.
• Continuously update your data science skills and progress.
• Iterate with the engineering teams to improve the quality of telemetry data
• Accelerate the speed of learning and discovery for the engineering teams across our portfolio.

Requirements

• Master’s Degree, or higher, in Data Science, Statistics, Computer Science, Math, or similar quantitative field
• Demonstrated experience with machine learning, statistical analysis, predictive modeling, time series analysis, and/or customer segmentation
• Strong data discovery and analysis skills
• Experience with big data using technologies like Hadoop, Spark, NoSQL and/or traditional relational databases
• Experience with ML packages & tools
• Experience with a variety of relevant languages (Python, Java, Scala, Pig, SQL)

Preferred qualifications

• Deep learning (Tensor Flow, Keras) is a strong plus
• AWS, EC2 Experience is a plus
• Experience with data visualization (ggplot2, d3, Tableau)
• Familiarity with Agile/Scrum
• Familiarity with software as a service, API development
• Familiarity with standard software development practices (source control, unit testing, code reviews, automation, performance monitoring)

SAP'S DIVERSITY COMMITMENT
To harness the power of innovation, SAP invests in the development of its diverse employees. We aspire to leverage the qualities and appreciate the unique competencies that each person brings to the company.
SAP is committed to the principles of Equal Employment Opportunity and to providing reasonable accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team (Americas: [email protected] or [email protected] , APJ: [email protected] , EMEA: [email protected] ). Requests for reasonable accommodation will be considered on a case-by-case basis.
EOE AA M/F/Vet/Disability:
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, gender, sexual orientation, gender identity, protected veteran status or disability.
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