Offers “Siemens”

Expires soon Siemens

Data Analyst

  • Internship
  • SINGAPORE

Job description

Job Description

Do you want to contribute to the future of healthcare? As Siemens Healthineers values those who dedicate their energy and passion to this cause, our company's name is dedicated to our employees. It's their pioneering spirit, blended with our long history of engineering in the ever-evolving healthcare industry that truly makes us unique as an employer.

We offer you a flexible and dynamic environment and the space to stretch beyond your comfort zone in order to grow both personally and professionally. Sound interesting?

Then come in and join our global team as Data Analyst. You will be involve with research collaboration projects and internal data analysis projects.

Your mission and responsibilities:

· 

You work with our research partners on various machine learning based projects for healthcare applications on the analysis (collection and analysis) of

·  Hospital workflow related predictive models or software to improve patient management, patient data, treatment methods and clinical outcomes.
·  Develop software for these applications that can be deployed by our partners.
· 

· 

You support AI projects, which includes collection of patient case, development of relevant tools to facilitate such activities and evaluation of prototypes.

· 

You will conduct data exploration: identify relevant data sets, new relations among data sets, and integrate such data in analysis

· 

You will develop and configure marketable analytical solutions such as dashboards and data visualizations (product grade quality).

· 

You will define and provide requirements to IT infrastructure

· 

You will collaborate with Enterprise IT, service and product business units to maintain analytical solutions

· 

You will implement and manage big data analytics projects and present results to stakeholders inside and outside the company

To find out more about the specific business, have a look at https://www.healthcare.siemens.com.sg/

Your qualifications and experiences:

· 

You hold a Bachelor or Master of Science in computer science, engineering, statistics or applied mathematics

· 

You have good knowledge of various statistical models

· 

You have knowledge of neural networks and machine learning

· 

You have knowledge of computer and programming skills (C/C++, python, R, etc.)

Your personality and skills:

· 
You are self- driven with strong multi-tasking skills and thrives on challenges

· 
You have high accuracy and strong attention to detail and a strong analytical mind

· 
You have good organizational skills. Ability to work and collaborate with different team across the company

· 
You have excellent (spoken and written) communication skills

· 
You have good interpersonal skills

· 
You have interest in a career in healthcare data analytics and medical imaging

Being part of our team:

Siemens Healthineers is a leading global medical technology company. More than 48,000 dedicated colleagues in over 70 countries are driven to shape the future of healthcare. An estimated 5 million patients across the globe benefit every day from our innovative technologies and services in the areas of diagnostic and therapeutic imaging, laboratory diagnostics and molecular medicine, as well as digital health and enterprise services.

Your cultural fit:

Our unique team spirit arises from embracing different perspectives, open debate, and the will to challenge conventions. Change is a constant aspect of our work. We aspire to lead the change in our industry rather than just react to it. That's why we want you to seek, implement and celebrate your best ideas.

To all recruitment agencies:

Siemens Healthineers does not accept agency resumes. Please do not forward resumes to our jobs alias, employees or any other company location. Siemens Healthineers is not responsible for any fees related to unsolicited resumes.

Organization: Siemens Healthineers

Company: Siemens Healthcare Pte Ltd

Experience Level: Early Professional

Job Type: Full-time

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