- The LA AI & Data Center of Excellence seeks a highly skilled and motivated Senior Data Scientist to join our team.
- This role focuses on developing and deploying cutting-edge AI solutions emphasizing automation software engineering best practices and production-ready code.
- This role requires proficiency in Python programming and experience with various machine learning deep learning generative and agentic AI.
- The successful candidate will work on projects across diverse business units directly impacting critical decision-making and driving innovation.
- You will be able to lead the development of intelligent systems with a strong emphasis on software and AI engineering best practices automation and continuous delivery.
Qualifications :
Experience and Knowledge (Mandatory):
- Bachelors or Masters degree in Computer Science Data Science Computer Engineering Software Engineering Information Technology Mathematics or Physics. (Ph.D. in a relevant field is a plus).
- Proven Track Record: Deep experience as an individual contributor in Data Science Machine Learning or AI Engineering consistently delivering high-impact AI solutions in complex real-world enterprise environments.
- Business Acumen & Leadership: Strong ability to assess the business impact of AI models including cost-benefit analysis ROI estimation and value tracking post-deployment. Proven ability to mentor junior data scientists and guide technical decisions within agile squads.
- Expert-Level Python: Advanced proficiency in Python including Pandas Polars NumPy Scikit- learn TensorFlow PyTorch and Keras. Experience with Flask/FastAPI for RESTful API development.
- Software Engineering Excellence: Strong foundation in OOP Clean Code principles and modular design. Hands-on experience with version control (Git) unit testing CI/CD pipelines and containerization (Docker Kubernetes).
- End-to-End ML Lifecycle: Deep expertise in data preparation model training tuning inference deployment monitoring and retraining.
- Data Handling & Integration: Expertise in ETL processes from various sources (relational/non- relational databases cloud storage APIs). Experience with SQL NoSQL vector databases and integrating AI outputs with core enterprise systems (e.g. ERPs).
- Core ML & NLP: Strong grasp of supervised and unsupervised learning techniques (regression classification clustering time series). Solid foundation in Natural Language Processing (NLP) techniques and libraries.
- Generative AI: Practical experience with LLMs prompt engineering fine-tuning and architecting RAG pipelines.
- Cloud Platforms: Experience designing and operating data pipelines and deploying models on major cloud platforms Azure (preferred) GCP or AWS leveraging their respective AI/ML services.
- Languages: Native/fluent Portuguese (Brazilian) and fluent English. German is a strong plus.
- Profile & Working Method: Team player with strong analytical thinking proactive problem- solving skills and resilience. Self-taught mentality with a continuous passion for staying current with AI advancements.
- Communication: Exceptional ability to collaborate in cross-functional teams and translate complex technical insights into accessible actionable information for diverse business stakeholders.
Experience and Knowledge (Desirable):
- Enterprise AI Ecosystems & Agentic Workflows: Experience architecting secure solutions using platforms like Google Gemini Enterprise Microsoft Copilot Studio or n8n. Hands-on experience building multi-agent systems using frameworks (LangChain AutoGen LangFlow) and communication protocols (MCP WebMCP A2A).
- Hyperautomation & Cognitive Technologies: Experience moving beyond simple task automation by leveraging an integrated ecosystem of Low-Code/No-Code AI/ML and Process Mining to architect end- to-end business workflows.
- Advanced MLOps & Data Engineering: Experience with MLFlow Kubeflow Jenkins GitHub Actions or Azure DevOps. Familiarity with big data technologies (Spark Hadoop Databricks) and data warehousing.
- Computer Vision: Experience applying deep learning to computer vision use cases.
- Knowledge Graphs: Experience with graph-based data representations (Neo4j RDF SPARQL) or graph neural networks for reasoning and relationship modeling.
- Domain Expertise: Specialized knowledge in specific industries HR marketing laws or supply chain.
Informações adicionais :
Benefícios da Bosch
The LA AI & Data Center of Excellence seeks a highly skilled and motivated Senior Data Scientist to join our team.This role focuses on developing and deploying cutting-edge AI solutions emphasizing automation software engineering best practices and production-ready code.This role requires proficien...
- The LA AI & Data Center of Excellence seeks a highly skilled and motivated Senior Data Scientist to join our team.
- This role focuses on developing and deploying cutting-edge AI solutions emphasizing automation software engineering best practices and production-ready code.
- This role requires proficiency in Python programming and experience with various machine learning deep learning generative and agentic AI.
- The successful candidate will work on projects across diverse business units directly impacting critical decision-making and driving innovation.
- You will be able to lead the development of intelligent systems with a strong emphasis on software and AI engineering best practices automation and continuous delivery.
Qualifications :
Experience and Knowledge (Mandatory):
- Bachelors or Masters degree in Computer Science Data Science Computer Engineering Software Engineering Information Technology Mathematics or Physics. (Ph.D. in a relevant field is a plus).
- Proven Track Record: Deep experience as an individual contributor in Data Science Machine Learning or AI Engineering consistently delivering high-impact AI solutions in complex real-world enterprise environments.
- Business Acumen & Leadership: Strong ability to assess the business impact of AI models including cost-benefit analysis ROI estimation and value tracking post-deployment. Proven ability to mentor junior data scientists and guide technical decisions within agile squads.
- Expert-Level Python: Advanced proficiency in Python including Pandas Polars NumPy Scikit- learn TensorFlow PyTorch and Keras. Experience with Flask/FastAPI for RESTful API development.
- Software Engineering Excellence: Strong foundation in OOP Clean Code principles and modular design. Hands-on experience with version control (Git) unit testing CI/CD pipelines and containerization (Docker Kubernetes).
- End-to-End ML Lifecycle: Deep expertise in data preparation model training tuning inference deployment monitoring and retraining.
- Data Handling & Integration: Expertise in ETL processes from various sources (relational/non- relational databases cloud storage APIs). Experience with SQL NoSQL vector databases and integrating AI outputs with core enterprise systems (e.g. ERPs).
- Core ML & NLP: Strong grasp of supervised and unsupervised learning techniques (regression classification clustering time series). Solid foundation in Natural Language Processing (NLP) techniques and libraries.
- Generative AI: Practical experience with LLMs prompt engineering fine-tuning and architecting RAG pipelines.
- Cloud Platforms: Experience designing and operating data pipelines and deploying models on major cloud platforms Azure (preferred) GCP or AWS leveraging their respective AI/ML services.
- Languages: Native/fluent Portuguese (Brazilian) and fluent English. German is a strong plus.
- Profile & Working Method: Team player with strong analytical thinking proactive problem- solving skills and resilience. Self-taught mentality with a continuous passion for staying current with AI advancements.
- Communication: Exceptional ability to collaborate in cross-functional teams and translate complex technical insights into accessible actionable information for diverse business stakeholders.
Experience and Knowledge (Desirable):
- Enterprise AI Ecosystems & Agentic Workflows: Experience architecting secure solutions using platforms like Google Gemini Enterprise Microsoft Copilot Studio or n8n. Hands-on experience building multi-agent systems using frameworks (LangChain AutoGen LangFlow) and communication protocols (MCP WebMCP A2A).
- Hyperautomation & Cognitive Technologies: Experience moving beyond simple task automation by leveraging an integrated ecosystem of Low-Code/No-Code AI/ML and Process Mining to architect end- to-end business workflows.
- Advanced MLOps & Data Engineering: Experience with MLFlow Kubeflow Jenkins GitHub Actions or Azure DevOps. Familiarity with big data technologies (Spark Hadoop Databricks) and data warehousing.
- Computer Vision: Experience applying deep learning to computer vision use cases.
- Knowledge Graphs: Experience with graph-based data representations (Neo4j RDF SPARQL) or graph neural networks for reasoning and relationship modeling.
- Domain Expertise: Specialized knowledge in specific industries HR marketing laws or supply chain.
Informações adicionais :
Benefícios da Bosch
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