Senior Data Scientist – AI, Data Engineering & Intelligent Automation

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 Key Responsibilities: - Data Analytics/Pyspark/Azure data bricks - Pipeline Design & Development: Build, monitor, and maintain robust, scalable batch and real-time ETL/ELT pipelines using PySpark, SQL, Delta Lake, and Auto Loader. - Data Governance & Security: Enforce data access policies, row/column-level security, and lineage tracking using Databricks Unity Catalog to protect PII and maintain compliance - Orchestration & Workflow Automation: Schedule and orchestrate multi-task jobs using Databricks Workflows (Lakeflow Jobs) or external schedulers (e.g., Apache Airflow, Azure Data Factory) - Data Quality Assurance: Define and integrate automated data quality rules, validation checks, and testing frameworks (e.g., Great Expectations, Delta Live Tables expectations) directly into pipelines - Big Data handling :Design and implement scalable data ingestion, transformation, and processing pipelines. - Automate data collection, validation, and integration workflows. - Ensure data quality, reliability, and governance across the data ecosystem. - Interface with diverse enterprise data sources including databases, APIs, cloud platforms, files, streaming systems, and third-party applications. - Analyze structured and unstructured data to derive actionable insights and recommendations. - Design experiments, evaluate data performance, and continuously improve solution effectiveness.Apply advanced analytics techniques to support business decision-making. - Data Visualization & Business Insights. Build intuitive dashboards and visualizations to communicate insights effectively. - Translate technical findings into business-friendly recommendations. - Support leadership teams with data-driven decision-making.AI, GenAI & Agentic Solutions. - Design and develop AI-powered applications using modern Large Language Models (LLMs). - Build Agentic AI workflows and intelligent assistants for enterprise use cases. - Implement Model Context Protocol (MCP)-based integrations and orchestration frameworks. - Develop Retrieval-Augmented Generation (RAG) and enterprise knowledge solutions. - Deployment, Cloud & Infrastructure Deploy AI and analytics solutions across cloud and on-premises environments. - Design scalable solution architectures on Azure, AWS, GCP, or hybrid platforms. - Containerize applications using Docker. - Collaborate with infrastructure and DevOps teams to ensure production-grade deployments. - Stakeholder Management & Technical Leadership. Work closely with business stakeholders to understand requirements and define solution roadmaps. Lead technical discussions and provide architectural guidance. - Present complex technical concepts to both technical and non-technical audiences. - Mentor junior team members and promote engineering best practices.   Required Technical Skills: - Data Science & Analytics, Machine Learning, Statistical Modeling, Predictive Analytics, Data Mining, Feature Engineering Model Evaluation and Optimization. - Programming & Development: Python (Mandatory), SQL (Mandatory) - Strong scripting and automation skills. REST APIs and system integrations, Version control systems (Git)Data Engineering, ETL/ELT Development, Data Pipeline Design, Data Warehousing Concepts, Workflow Automation, Structured and Unstructured Data Processing, Data Visualization, Power BI, Tableau, Looker, or equivalent platforms, Dashboard Development, Data Storytelling, Cloud & Infrastructure, Azure, AWS, or GCP, Docker, Kubernetes, CI/CD Concepts, Solution Deployment and Monitoring AI & Generative AI, Large Language Models (LLMs)Claude, OpenAI, and related AI platforms, Agentic AI Frameworks , Model Context Protocol (MCP), Prompt Engineering, RAG Architectures, AI Application Deployment. Qualifications : - Bachelor's Degree (BE/BTech) in Computer Science, Information Technology, Data Science, Engineering, Mathematics, Statistics, or a related field. - Master's Degree is an added advantage. - 8+ years of experience in Data Science, Data Engineering, AI, or Analytics domains. Proven experience delivering end-to-end solutions from data acquisition B.E 6 to 8 years