Siemens Careers

Data Analyst - Machine Learning

Alpharetta, Georgia
Customer Services

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English (US)

Job Description

Division: Process Industries and Drives
Business Unit: Process Automation
Requisition Number: 231743
Primary Location: United States-Georgia-Alpharetta
Assignment Category: Full-time regular
Experience Level: Mid level
Education Required Level: Bachelor's Degree
Travel Required: 10%

Division Description:

Siemens is a global technology powerhouse that has stood for engineering excellence, innovation, quality, reliability and internationality 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, Healthcare and Financial Services.

The Siemens Digital Factory Division offers a comprehensive portfolio of seamlessly integrated hardware, software and technology-based services in order to support manufacturing companies worldwide in enhancing the flexibility and efficiency of their manufacturing processes and reducing the time to market of their products.

For more information, please visit:
http://www.siemens.com/businesses/us/en/digital-factory.htm



Job Description:

If you really want to make a difference with your data analytical expertise – make it with us

Siemens Industry, Inc. is a US subsidiary of Siemens AG, a global powerhouse in electronics and electrical engineering operating in the industry, energy, healthcare, and infrastructure & cities sectors. For more than 165 years, Siemens has built a reputation for leading-edge innovation and the quality of its products, services and solutions.

The Process Industries and Drives (PD) division of Siemens Industry is a reputed global provider of future-proof automation and drive technology, industry software and services based on innovative technology platforms. Siemens PD’s Digital Enterprise Lab focuses on the development of innovative, data-driven, cloud enabled software applications for industrial digitalization using cutting edge technologies.

If you meet the requirements of this position and want to work for a world-class company with a great marketplace reputation, apply today.

Position Overview

 

Siemens Industry, Inc. is hiring data analysts for the US branch of its Process Industries and Drives (PD) division’s Digital Enterprise Lab, located in Alpharetta GA to work on machine learning, data mining, and statistical modeling for predictive, prescriptive, diagnostic and descriptive industrial analytics. In this role, you will be part of Data Analytics and Development team and take responsibility for investigating state of the art techniques in advance machine learning and statistical modeling. You and your team will be expected to design, develop, and deploy state of the art, scalable innovative analytics applications in a set of industrial verticals e.g. Oil & Gas, Chemicals, Glass, Pharma, Pulp & Paper etc. You will be expected to work with a diverse set of data sources, such as time series data, spatial, graph data, semi-structured and unstructured data, and build statistical/machine-learning models in support of on-demand, real-time analytic services.

You will report directly to the Head of Data Analytics and Development.

Responsibilities – Leadership, Customer Orientation, Innovative Mindset, Ownership, Problem Solving

  • You solve business problems with machine learning methods, signal processing, optimization methods and relevant techniques and create data analytics solutions based on business requirements.
  • You design and implement robust data driven algorithms on a massively parallel platform (i.e. Hadoop, HBase, MapReduce, AWS).
  • You combine signal processing, machine learning and knowledge based methods in order to realize i.e. anomaly detection, fault classification, diagnosis and prognosis.
  • In an agile process you closely work together with software engineers and domain experts in order to develop data analytics solutions for process industry and power generation

 Required Knowledge/Skills, Education, and Experience

  • You hold a degree (Bachelor, Master or PhD) in computer science, (applied) mathematics, physics or engineering (ideally with a focus on machine learning)
  • You have several years of professional experience in the field of data science, machine learning or statistics
  • You have extensive knowledge in data mining processes, signal processing, image processing, time series analysis or related fields
  • You have experience in one or more of the following data analytics frameworks or libraries and programming (i.e. KNIME, Python, R, Anaconda, Scikit-Learn, Tensorflow, Java)
  • Ideally, you have first experience with massively parallel processing i.e. Hadoop, Spark, Pig, Hive, AWS etc.
  • You are proficient in English; Spanish language skills would be an advantage.

Qualified Applicants must be legally authorized for employment in the Unites States. Qualified Applicants will not require employer sponsored work authorization now or in the future for employment in the United States.


*LI-CYL



Equal Employment Opportunity Statement
Siemens is an Equal Opportunity and Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, protected veteran or military status, and other categories protected by federal, state or local law.

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Applicants and employees are protected under Federal law from discrimination. To learn more, Click here.

Pay Transparency Non-Discrimination Provision
Siemens follows Executive Order 11246, including the Pay Transparency Nondiscrimination Provision. To learn more, Click here.



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