Data Scientist L1 Iits Nits Iiits Or Those With Relevant Master S And Ph D Degrees 6 Positions

## About the Role As a Data Engineer at EveoAI, you will be responsible for handling and optimizing our data infrastructure, ensuring efficient data processing and integration. You will work closely with our AI/ML engineers and data analysts to support the development of our domain-specific LLM and other AI-driven features. ## Key Responsibilities ### Data Management - Manage and maintain large datasets and data warehouses, ensuring data integrity and availability. ### Data Mining - Extract information from diverse sources, including databases, documents, and external APIs. - Employ advanced data mining techniques to discover hidden patterns. ### Data Cleaning - Perform data cleaning and preprocessing to ensure high-quality data for analysis and model training. - Design and implement data cleaning and preprocessing workflows. - Detect and resolve missing, duplicate, inconsistent, and corrupted data. - Establish data validation, quality assurance, and monitoring processes. - Maintain data integrity and accuracy across all datasets. ### ETL/ELT Processes - Design, develop, and maintain efficient ETL/ELT pipelines to support data ingestion, transformation, and loading. ### Collaboration - Work closely with AI/ML engineers and data analysts to understand data requirements and deliver solutions that meet their needs. ### Performance Optimization - Continuously monitor and optimize data processes for performance, scalability, and reliability. ### Documentation - Maintain comprehensive documentation of data processes, pipelines, and infrastructure. ### Feature Engineering & Development - Design, create, and optimize features for machine learning and AI applications. - Perform exploratory data analysis (EDA) to identify predictive patterns and relationships. - Build reusable feature stores and feature transformation pipelines. - Continuously improve feature quality and model performance through experimentation. ### Data Management & Governance - Develop and maintain scalable data architecture and data management systems. - Implement data cataloging, metadata management, and version control practices. - Define data governance standards, policies, and documentation. - Ensure compliance with privacy, security, and regulatory requirements. ### Machine Learning & AI Support - Prepare datasets for model training, validation, and testing. - Work closely with AI/ML engineers to optimize data pipelines and model inputs. - Monitor model performance and identify data-related improvement opportunities. - Support model retraining and continuous learning initiatives. ### Analytics & Insights - Analyze large datasets to identify trends, patterns, and business opportunities. - Develop dashboards, reports, and data visualizations for stakeholders. - Present findings and recommendations to technical and non-technical teams. - Translate business problems into data-driven solutions. ### Data Infrastructure & Automation - Build scalable ETL/ELT pipelines and automated workflows. - Optimize database performance and data storage solutions. - Work with cloud-based data platforms and big data technologies. - Support deployment and monitoring of production data pipelines. ## Qualifications ### Educational Background - Bachelor's degree in Computer Science, Engineering, or a related field from IITs, NITs, IIITs, or equivalent. Relevant Master's or Ph.D. degrees are also considered. ### Technical Skills - Proficiency in SQL and experience with database management systems (e.g., MySQL, PostgreSQL). - Knowledge of data warehousing concepts and tools. ### Programming Skills - Experience with programming languages such as Python or Java for data processing tasks. ### Data Processing - Familiarity with ETL/ELT tools and frameworks (e.g., Apache Airflow, Talend). ### Problem-Solving - Strong analytical and problem-solving skills, with attention to detail. ### Collaboration - Excellent communication and teamwork skills, with the ability to work effectively in a collaborative environment. ## Preferred Qualifications - Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and their data services. - Knowledge of big data technologies (e.g., Hadoop, Spark). - Understanding of data security and privacy best practices. ## What We Offer - **Innovative Environment**: Work on cutting-edge AI and AR technologies in a dynamic and fast-paced environment. - **Career Growth**: Opportunities for professional development and career advancement. - **Collaborative Culture**: Join a passionate and collaborative team committed to innovation and excellence.