Data Scientist (Python, Problem Solving, Machine Learning)

Overview Job Description - Data Scientist (Python, Problem Solving , Machine Learning) (MER0003L3Q)

Data Scientist (Python, Problem Solving , Machine Learning) Group : Mercedes-Benz Group AG

Description

About Us

At Mercedes-Benz, we don’t just build cars, we create great software. We develop tomorrow’s mobility together in our product lines, pushing the digitization of the Mercedes-Benz Group AG forward. As a tech company, we are agile, innovative, and always keep our finger on the pulse of change. This is why inner source, FOSS, secure code, DevOps, infrastructure as code (IaC), data analytics, artificial intelligence, and many more are core components of our daily work.

IT is our passion, and we move toward a bright future, sometimes quickly, sometimes creatively but always together.

We believe in integrity, trust, and transparency as part of our flexible work culture, with a strong emphasis on teamwork and the learning process, making mistakes, and achieving continuous progress together in all products we create and develop within the Mercedes-Benz Group.

Our workplace is anywhere

• with a fast connection whether remotely at home, at your favorite café, or at our integrated office at Wisma Mercedes-Benz, which comes with an LRT station at its doorstep, an al fresco cafeteria, ample greenspaces, and free parking.

Responsibilities

Task Description : Advising the customer on the use of AI, capturing the requirement and translating the requirement into suitable mathematical models.

Data preparation, exploratory data analysis and statistical analysis.

Conception of labelling processes.

Selection, implementation and configuration of suitable (machine learning / semantic) models and procedures.

Conception and implementation of automated pipelines for model creation and quality assurance.

Conception and implementation of infrastructure and software to integrate AI into software products in a scalable way.

Ensuring compliance with applicable rules in the areas of data, AI and IT security compliance.

Documentation and communication of the procedures and results in a target group-adequate form.

Responsibility and Scope for decision-making

Independent consulting of the customer to identify new areas of application of AI.

Independent consulting of the customer on the use of AI, on capturing the requirement and translating the requirement into suitable mathematical models.

Independent data preparation, exploratory data analysis and statistical analysis, conception of labeling processes.

Independent selection, implementation and configuration of suitable (machine learning / semantic) models and procedures, also on the basis of scientific literature.

Conception and implementation of automated pipelines for model creation and quality assurance.

To integrate the design and implementation of infrastructure and software and AI into software products in a scalable manner.

Independent assurance of compliance with the relevant rules from the areas of data, AI and IT security.

Networking and sharing of knowledge and experience within the company, within the Group and beyond.

Qualifications

Qualifications / Experience :

Minimum of 5 years’ working experience in a related field is required.

Bachelor’s Degree in Computer Science, Applied Mathematics, Engineering, or any other technology related field.

Experience with Agile methodologies

Experience with Enterprise technologies

Experience with Product Oriented Teams

Programming or Data Architecture related certification

Specific knowledge / Skill :

Analytical, passionate and drives technology and product quality

Result-oriented thinking and action

Has a broad and deep understanding of AI methods and their applicability in day-to-day operations.

Possesses broad and constantly expanded knowledge of mathematical and formal methods with their strengths and weaknesses.

Possesses broad and constantly expanded knowledge methods of data preparation, exploratory data analysis, data visualizations and statistical analysis.

Ability to implement and configure machine learning / semantic models close to the state of research.

Ability to design and implement automated pipelines for model creation and quality assurance.

Knowledge of the conception and implementation of infrastructure to integrate software and AI into software products in a scalable way.

Knowledge of applicable rules from the areas of data, AI and IT security compliance.

Ability to document and communicate the procedures and results in target group-adequate form.

Technical SQL / noSQL, Python or R, Spark, Apache libraries, Machine Learning algorithms, Cloud Computing and Data Architectures

#J-18808-Ljbffr