Candidates willing to learn alternates can apply Data Scientist Data Analyst Data Engineers Collect, clean, and preprocess structured and unstructured datasets. Perform exploratory data analysis (EDA) to identify patterns, trends, and insights. Assist in building and testing machine learning models under the guidance of senior team members. Generate reports, dashboards, and visualizations using tools such as Tableau, Power BI, or Matplotlib . Work with cross-functional teams (business, engineering, product) to support data-driven decision-making. sr professionals Collect, clean, and transform large-scale datasets from multiple sources. Perform exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights. Build, validate, and deploy machine learning models (classification, regression, recommendation, NLP, deep learning). Collaborate with data engineers to ensure data availability, scalability, and quality. Work closely with business and product teams to define problems, identify opportunities, and provide data-driven recommendations. Develop and maintain dashboards, reports, and visualization tools (Tableau, Power BI, or similar). Stay updated with latest ML/AI research, tools, and frameworks to improve existing solutions. Document workflows, models, and results for reproducibility and knowledge sharing. Data Engineer will manage data pipelines, write optimized SQL queries, automate data processing tasks using Python, and ensure data accuracy and integrity through collaboration and automated testing. Responsibilities also include overseeing data governance and compliance.