Data Scientist

Position: Data Scientist

Notice Period: Immediate Joiner

Experience: 5\+ Years

Key Responsibilities

 Collect, clean, and preprocess data from diverse sources to ensure quality and

accuracy.

 Develop and refine statistical models and Machine Learning (ML) algorithms to solve real-world problems.

 Collaborate with cross-functional teams (e.g., data engineering, product, and business) to identify and understand analytical needs.

 Perform exploratory data analysis (EDA) to uncover patterns, trends, and relationships in datasets.

 Evaluate model performance using appropriate metrics, and iterate to optimize accuracy and efficiency.

 Document analyses, methodologies, and best practices to maintain clear records for

future reference.

 Stay up-to-date with emerging AI/ML technologies and actively explore new

approaches—especially in the areas of deep learning, Generative AI, and Large

Language Models (LLMs).

 Present findings and insights to both technical and non-technical stakeholders in a clear, concise manner.

Qualifications

 Design and Build Data Pipelines: Assist in the development of reliable, efficient

ETL (Extract, Transform, Load) and/or ELT pipelines that move data from a variety

of internal and external sources into data storage systems.

 Data Integration and Collaboration: Work closely with data scientists, data

analysts, and software engineers to ensure data is readily available and properly

structured for analysis and modeling.

 Data Quality and Validation: Implement quality checks, error handling, and

monitoring processes to ensure the reliability and accuracy of data.

 Optimize Performance: Contribute to the optimization of data pipelines and

database queries to handle high-volume data and achieve better performance and

scalability.

 Maintain Documentation: Develop and maintain technical documentation for data

systems, pipelines, and processes to keep the team aligned and informed.

 Security and Compliance: Support efforts to ensure secure data handling and

compliance with relevant regulations and industry best practices.

 Continuous Learning and Innovation: Stay informed about emerging data

engineering tools, techniques, and technologies; share learnings with the team; and

implement improvements where applicable

Skills: eda,machine learning,gen ai,data scientist,python,ml,sql,generative ai,llm,models,ai/ml,deep learning