Data Scientist L1 | IITs, NITs, IIITs, or those with relevant Master’s and Ph.D. degrees. - 6 Positions

Job Description: 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.

Required Skills & Qualifications

• Strong proficiency in Python, SQL, and data analysis libraries (Pandas, NumPy, Scikit-learn).
• Experience with data preprocessing, feature engineering, and machine learning workflows.
• Knowledge of data warehousing, ETL pipelines, and database systems.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with big data technologies (Spark, Hadoop, Databricks) is a plus.
• Understanding of data governance, data quality frameworks, and security best practices.
• Strong analytical, problem-solving, and communication skills.

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.