Data Scientist at Bosch Group

Bangalore, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

30 Apr, 26

Salary

0.0

Posted On

30 Jan, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Machine Learning, Python, R, Julia, TensorFlow, PyTorch, Scikit-learn, Time-Series Databases, Streaming Data Platforms, Industrial Protocols, Cloud Environments, Predictive Maintenance, Digital Twin, Data Integration, Anomaly Detection

Industry

Software Development

Description

Company Description Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region. Job Description Roles & Responsibilities : We are looking for a Data Science Engineer to join our Industrial Digital Twin Solutions team. The role will focus on developing AI/ML models, data pipelines, and analytics frameworks to simulate, predict, and optimize industrial systems in a digital twin environment. You will work closely with cloud architects, IoT engineers, and domain experts to transform raw industrial data into actionable insights that drive efficiency, reliability, and innovation. Qualifications Educational qualification: Bachelor’s/Master’s in Data Science, Computer Science, AI/ML, or related field. Experience in data science or ML engineering, preferably in industrial or IoT domains. Strong programming skills in Python, R, or Julia with libraries (TensorFlow, PyTorch, Scikit-learn). Experience with time-series databases (InfluxDB, TimescaleDB) and streaming data platforms (Kafka, Azure Event Hub, AWS Kinesis). Knowledge of industrial protocols (OPC-UA, Modbus, MQTT) for data integration. Hands-on experience deploying ML models in cloud environments (AWS, Azure, GCP). Experience : Fresher can also apply Mandatory/requires Skills : Data Engineering & Modeling Build and optimize data pipelines for ingestion and preprocessing of industrial IoT, sensor, and operational data. Design and implement time-series data models and predictive algorithms to support digital twin simulations. Develop physics-informed ML models for real-world process simulation and anomaly detection. Analytics & Insights Create predictive maintenance models, asset life-cycle estimations, and optimization algorithms. Apply machine learning and deep learning to process, energy, and manufacturing datasets. Support what-if analysis and scenario simulations within the digital twin framework. Collaboration & Integration Work with cloud architects to deploy ML models into cloud-native digital twin platforms (Azure Digital Twins, AWS IoT TwinMaker, Siemens/Mindsphere). Collaborate with mechanical/electrical engineers to integrate domain-specific physics models with data-driven models. Partner with product teams to design dashboards and visualization of model results for decision-makers. Governance & Best Practices Ensure data quality, governance, and compliance with industry standards (ISO 27001, GDPR, etc.). Document ML models, experiments, and pipelines for reproducibility and auditing. Contribute to innovation by exploring advanced AI/ML techniques (GNNs, reinforcement learning, digital twin physics integration). Preferred Skills : Experience with digital twin platforms (Azure Digital Twins, AWS IoT TwinMaker, Dassault Systemes, Siemens). Knowledge of physics-based modeling, simulation software (MATLAB, Simulink, Ansys, Modelica). Familiarity with edge ML deployment and optimization. Publications, patents, or contributions to AI/ML for Industry 4.0. Legal Entity: Bosch Global Software Technologies Private Limited

Responsibilities

The Data Scientist will develop AI/ML models, data pipelines, and analytics frameworks to optimize industrial systems in a digital twin environment. Collaboration with cloud architects and domain experts is essential to transform raw data into actionable insights.