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.