Siemens Business Program Intern in Hoffman Estates, Illinois

Business Program Intern

Locations:Hoffman Estates, Illinois

Job Family: Research & Development

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English (US)

Job Description

Division: Siemens Healthineers

Business Unit: Advanced Therapies

Requisition Number: 212051

Primary Location: United States-Illinois-Hoffman Estates

Assignment Category: Full-time temporary

Experience Level: Entry level

Education Required Level: Master's Degree

Travel Required: No

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, Healthineers and Financial Services.

With 45,000 employees Siemens Healthineers is one of the world’s largest suppliers of technology to the healthcare industry and a leader in medical imaging, laboratory diagnostics and healthcare IT. All supported by a comprehensive portfolio of clinical consulting, training, and services available across the globe and tailored to customers’ needs. So that more people can have a life that is longer, richer, and more filled with happiness.

For more information, please visit: http://www.usa.siemens.com/healthineers

Job Description:

Job Description: Data Science Intern

Position Overview

Siemens Healthineers, Advanced Therapy (AT) division is looking for outstanding candidates to participate in our Business Internship program at our Hoffman Estates, IL location.

Advanced Therapy division is one of the top-performing business units within Siemens Healthineers, a leading supplier of innovative, market-driven solutions.

Job Description

AT is looking for a passionate data science intern who can stand to the challenge of innovating sophisticated machine-learning based techniques for deep data analysis to provide key actionable insights to aid internal and external stakeholders in decision making, enhancing efficiency and bringing more value to our customers. As part of the team, you would be working at the intersection of Deep learning and BIG Data frameworks with the sole focus of creating white space opportunities for AT division. We are looking for an energetic intern candidate who can not only help our team design a great solution, but also can successfully put the idea into production. The intern candidate will have a bent for research with knowledge in NLP, pattern mining, anomaly detection, classification, and deep learning. The intern candidate should have good software development skills and be a great team player.

Description

· Use machine learning and statistical methods to develop models using large volumes of data to detect anomalies

· Develop code using object oriented programming languages to deploy the models in the production

· Mine patterns in the data to generate deep insights for data gaps and automatic data enrichment

· Design solutions to extract relevant information from text data using NLP and machine learning methods

Education Details

Currently enrolled in a MSc or PhD program in Machine-learning, Data Mining, Computer Science or similar

Key Qualifications

· Penchant for quick learning and product delivery

· Strong knowledge in various aspects of machine learning and NLP, such as deep learning, classification, regression, feature engineering, clustering, topic modeling, and statistical modeling.

· Hands on coding experience using object oriented programming (Java or Python)

· Good knowledge of working on Linux or related operating systems

· Proficiency with SQL or No-SQL databases and SQL query language

· Some experience working with machine learning platforms (H2O, Tensorflow, SciKit, or Spark MLLib) or Statistical packages is a plus

· Knowledge of big data technologies (Hadoop and Hive) is a plus

General Requirements

- Must be available to work at least 40 hours a week Monday-Friday.

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, ancestry, national origin, sex, sexual orientation, gender identity, age, marital status, family responsibilities, pregnancy, genetic information, protected veteran or military status, other categories protected by federal, state, or local law, and regardless of whether the qualified applicants are individuals with disabilities.

EEO is the Law:

Applicants and employees are protected under Federal law from discrimination. Click at http://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm here at http://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm to learn more. at http://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm

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.

EEO is the Law

Applicants and employees are protected under Federal law from discrimination. To learn more, Click here at https://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm .

Pay Transparency Non-Discrimination Provision

Siemens follows Executive Order 11246, including the Pay Transparency Nondiscrimination Provision. To learn more, Click here at https://www.dol.gov/ofccp/pdf/pay-transp_formattedESQA508c.pdf .