Data Scientist for (e-)Mobility Cloud Solutions at Bosch Group

Cluj-Napoca, , Romania -

Full Time

Start Date

Immediate

Expiry Date

08 Sep, 26

Salary

0.0

Posted On

10 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, PySpark, Databricks, Azure Data Services, Machine Learning, AI Modeling, ETL/ELT Pipelines, Statistical Analysis, Data Mining, Computer Vision, Time Series Analysis, Large Language Models, Git, Jira, Software Design

Industry

Software Development

Description

Company Description About Bosch Engineering Center Cluj Since its establishment in 2013, Bosch Engineering Center Cluj plays an essential role in the current transformation of the mobility sector. Through its extensive expertise in software, hardware & mechanical engineering, reliability engineering, as well as sales planning, the center contributes to the development of innovative products and services based on artificial intelligence (AI) applied in the fields of automated driving, electric and connected mobility. Thanks to the diverse professional and personal development opportunities, flexible working conditions, modern offices and laboratories in Cluj-Napoca, Jucu, Bucharest and Sibiu, we are one of the most desired employers among engineers and IT professionals in Romania. Our promise to our colleagues is rock-solid: we grow together, we enjoy our work, and inspire each other. Join us and see the difference. Work LikeABosch Job Description We are looking for a Data Scientist to join our team and help transform data into actionable insights that accelerate digitalization across the business. In this role, you will design, build, and operate scalable data and AI solutions, working with a global network of experts on impactful products, from intelligent reporting and data pipelines to AI-powered applications, computer vision, telemetry analytics, and event-detection systems. In your role you will: Design and implement statistical, machine learning, and AI models to solve real business and engineering problems. Build data-driven products and services across mobility-related domains, including cloud services, business process optimization, manufacturing analytics, and telemetry use cases. Ingest, process, and analyze diverse data sources, including relational databases, logs, sensor streams, and image data. Develop, test, and maintain reusable code libraries and production-grade data pipelines. Apply statistical and experimental methods to support root-cause analysis and decision-making. Take ownership across the full lifecycle of data solutions: discovery, prototyping, deployment, monitoring, and continuous improvement. Collaborate effectively in a multicultural, distributed team environment. Contribute to the adoption of leading-edge technologies and AI-powered applications. Technology Stack Programming and Data: Python, SQL, PySpark Data Platforms: Databricks, Azure Data Services Databases: Relational and non-relational databases (for example, Oracle, SQL Server, MongoDB) Data Processing: ETL/ELT pipelines, batch and streaming workflows AI/ML Tooling: Model development, evaluation, deployment, and monitoring tooling Collaboration: Git-based version control and issue tracking tools (for example, Jira) Qualifications Bachelor's degree or equivalent in a technical discipline (Computer Science, Mathematics, Physics, Engineering) or related field Strong foundation in statistics, machine learning, data mining, and AI/ML methodologies Hands-on experience with Python and SQL in professional or academic projects Proficiency with relational and non-relational database systems (for example, Oracle, SQL Server, MongoDB) Solid understanding of data structures, algorithms, and software design principles Experience designing and implementing ETL/ELT processes Demonstrated passion for solving complex data problems with an engineering mindset Excellent communication skills, analytical thinking, and ability to work effectively in diverse, distributed teams Strong initiative, attention to detail, and commitment to continuous learning Nice to Have Experience with big data platforms and architectures (for example, Databricks, cloud or on-premise solutions) Proven expertise in designing and operating complex, production-grade data systems Knowledge in specialized domains: time series analysis, computer vision, or image processing Familiarity with software documentation standards, issue tracking, and version control workflows Experience with Large Language Models (LLMs) or Large Multimodal Models (LMMs) in production applications Additional Information LikeABosch Benefits: Your work-life balance is valuable to us, so we offer you: 25 Days of annual leave, because work-life balance is essential to us; Flexible working hours and if you want to work from somewhere else than the office, our Home Office program helps you do that for up to 70% of your working time/month. Your health and well-being is important to us, so we have you covered: Medical subscription; Accident insurance; Sport activities and well-being initiatives. We believe in a Life-Long Learning approach, so you can take advantage of: Technical and soft skills trainings; Access to e-learning platforms; Local and Global career development programs; Opportunity to attend conferences; Bookster subscription. You will be part of a product company. You will contribute to developing end-to-end products that are delivered to Global OEMs. On top of these, we are offering: A monthly budget which can be used for several different services on an online benefit platform; Annual bonus; Lunch discounts. Ready to work LikeABosch? We live by our values, have an open feedback culture and there is plenty of room for innovative ideas. All because a team is only as valuable as its members. Legal Entity: Robert Bosch S.R.L.

Responsibilities

Design and implement scalable AI, machine learning, and statistical models to solve business and engineering problems in the mobility sector. Develop production-grade data pipelines and AI-powered applications, managing the full lifecycle from prototyping to monitoring.