Data Scientist - Advanced Analytics & AI

Siemens Energy; Abu Dhabi; On-site; AED 60,000 - 100,000; Full time

Job summary

Join a forward-thinking company dedicated to driving the energy transition as a Data Scientist specializing in advanced analytics and AI. This role offers the opportunity to work on innovative projects that leverage data science techniques to enhance operations in the energy sector. Collaborate with multidisciplinary teams, develop cutting-edge analytics solutions, and contribute to a sustainable future. If you are passionate about data, eager to learn, and ready to make a significant impact, this position is perfect for you.

Qualifications

• More than 3 years’ experience in data science, ideally in the energy industry.
• Strong programming skills in Python and/or R, with a focus on AI/ML.

Responsibilities

• Develop advanced analytics solutions using AI and machine learning techniques.
• Collaborate with teams to implement new data science and AI concepts.
• Drive the roll-out of AI/ML across the company through mentoring.

Skills

Data Science

Machine Learning

Artificial Intelligence

Python

R

Statistical Modelling

Cloud Computing

Analytical Skills

Interpersonal Skills

Communication Skills

Education

University degree in Computer Science

University degree in Mathematics

University degree in Physics

University degree in Engineering

Job description

Data Scientist - Advanced Analytics & AI

About the Role

Location: United Arab Emirates, Abu Dhabi
Company: Siemens Energy LLC
Organization: EVP Global Functions
Business Unit: Digital Core
Full / Part time: Full-time
Experience Level: Experienced Professional
Video URL - External Careers

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As a member of our global team for data & artificial intelligence, you work on challenging projects from all areas of the energy industry. Through combining strategic and business insights with the latest data science techniques, you help our business to drive maximum value from data and develop analytics solutions that provide strategic advantages in their day-to-day operations.

Passionate about the environment and climate change? Ready to be part of the future of the energy transition? The Siemens Energy Data & AI team plays a significant role in driving the energy transformation.

Honestly, we don’t have all the answers. Given the scale of the challenge, we need many perspectives to help reimagine the future. And we can’t do it alone.

Our team is looking for innovative, enthusiastic, and versatile data, digital, and AI professionals to drive us forward on this exciting venture.

LET’S TALK ABOUT YOU

Your profile

• More than 3 years’ work experience, ideally in the energy industry
• University degree in Computer Science, Mathematics, Physics, Engineering, or related field
• Excellent analytical skills and profound expertise in data science, machine learning, and artificial intelligence methods
• Programming skills in Python and/or R, good knowledge in statistical modelling, experience in deployment and cloud computing
• Strong customer focus and excellent interpersonal skills, open-minded and willing to learn
• Ability to collaborate effectively in multidisciplinary, multinational, and global teams
• Fluent in written and spoken English, with excellent communication and presentation skills
• Enthusiastic about data and analytics and eager to drive data use across all parts of a business and ecosystem

Your responsibilities

• Develop advanced analytics solutions leveraging AI and machine learning techniques for application along the value chain
• Work in cross-organizational, multi-disciplinary teams supporting the application and implementation of new data science and AI/ML concepts
• Drive the roll-out of AI/ML across the company through knowledge sharing, mentoring, and technical training support
• Stay up-to-date on latest developments in data science and AI/ML principles and theories to help the business make truly data-driven decisions
• Collaborate with industry and academic partners to drive research and leverage expertise in this field
• Document developed methods and processes and present results to stakeholders across the organization regularly