Big Data Software Engineer
Siemens Corporate Research
- Software Engineering
Siemens is a global technology powerhouse that has stood for engineering excellence, innovation, quality, reliability and internationally for more than 165 years. As a global technology company, Siemens is rigorously leveraging the advantages that this setup provides. To tap business opportunities in both new and established markets, the Company is organized in nine Divisions: Power and Gas, Wind Power and Renewables, Energy Management, Building Technologies, Mobility, Digital Factory, Process Industries and Drives, Healthineers and Financial Services. Our support functions are split into two organizations, Corporate Core and Corporate Services. These organizations provide essential services to better enable responsible and profitable growth. For more information, please visit: http://www.siemens.com/businesses/us/en/
For nearly 170 years, pioneering technologies and the business models developed from them have been the foundation of Siemens‘ success. Our central research and development unit, Corporate Technology (CT) plays an important role in this. Together with our global network of experts, we are a strategic partner to Siemens’ operative units and provide important services along the entire value chain – from research and development to production and quality assurance, as well as optimized business processes. Our support provided to the businesses in their research and development activities is ideally balanced with our own future-oriented research.
We at Corporate Technology are more than employees: We are actively helping to make people’s lives a little better every day. Would you like to be a part of that? Then join us. We offer you a high level of practical relevance as well as an opportunity to individually contribute your knowledge and your visions around the world. Whether you’re helping to develop products for the operating units or working in interdisciplinary projects for the business areas: At Corporate Technology you’ll be working in the heart of Siemens’ technological research together with the best.
We are seeking an Engineer in Big Data Analytics and Machine Learning to be part of our growing Information Integration and Business Intelligence (IBI) Team which is part of the exciting and world-wide distributed Technology Field of Business Analytics and Monitoring.
The Information Integration and Business Intelligence Research Group focuses on exciting cutting edge technologies in big data analytics and machine learning to gain exceptional business insights from tremendous amount of data and data-sources to improve the competitiveness of Siemens Business Units to generate innovative new products and business models used around the world.
This Engineer in Big Data Analytics will contribute to our research activities by applying modern data analytics and machine learning on variety of structured and unstructured data from wide area of different industries such as automation, energy, healthcare, building automation and mobility with the goal to improve business insights and help various business units to gain competitive advantage in their markets.
The Engineer in Big Data Analytics will be responsible for developing new algorithms and code prototypes as proof of concept in the new research area of Security, Safety and Compliance in collaboration with our security research group and also contribute to current analytics research for business analytics and monitoring.
• Research, design, and implement algorithms that power knowledge inference and online recommendations, based on Deep Learning/machine learning to consume various types of data.
• Dive into huge, noisy, and complex real-world behavioral data to produce innovative analysis and new types of predictive models of engineering behaviors and manufacturing processes performance.
• Explore the untapped potential of big data for design, engineering and analysis tasks and devise revolutionary approaches.
• Advance the state-of-the-art in the field, including generating patents and publications in top journals and conferences.
• Apply deep learning techniques to large-scale, real-world problems.
• Fast prototyping, feasibility studies, specification and implementation of data analysis product components.
• Working with customers to understand algorithm requirements and deliver high-quality solutions.
Required Knowledge/Skills, Education, and Experience
•Candidate must have Master degree with 3-5 years of Experiences in the field of Big Data Analytics.
•Strong proficiency in Software development in Java.
•Strong proficiency in Big Data tools and their configuration & setup is a plus.
•Strong proficiency in NoSQL databases (e.g MongoDB, Cassandra, etc).
•Strong proficiency in ETL tools (e.g Talend, Spring Batch, Informatica, etc).
•Proficiency in Knime, Hadoop and Spark
•Proficiency in parallel computing & distributed algorithms (e.g. Map-Reduce, CUDA, GPU)
•Capability for quick prototyping.
•Outstanding written and verbal communication skills in English are required.
•Excellent interpersonal skills and a can-do attitude.
•Strong collaboration skills and ability to thrive in a fast-paced environment.
•Flexibility and adaptability to work in a growing, dynamic team.
•Ability to work with controlled technology in accordance with US export control law required. Siemens may require candidates under consideration for employment opportunities to submit information regarding citizenship status to allow the organization to comply with specific US Export Control laws and regulations. Additional information on the US Export Control laws & regulations can be found on http://www.bis.doc.gov/index.php/policy-guidance/deemed-exports/deemed-exports-faqs?view=category&id=33#subcat34
Preferred Knowledge/Skills, Education, and Experience
•Degree in Computer Science or Information Technology preferred.
• Proficiency in security and compliance analytics preferred.
• Previous experience or knowledge in the field of probabilistic reasoning, uncertainty quantification, dimensionality reduction, decision trees, and design analysis is preferred.
• Previous experience or knowledge in the field of machine learning/deep learning.
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