Chief Manager - Guntur - Xpert Conexions

Description

Job Description

Role and Responsibilities:

• Analyze large datasets to identify trends, patterns, and insights.
• Validate findings using statistical methods to ensure they are reliable.
• Perform exploratory data analysis (EDA) to understand the data's structure and characteristics.
• Develop machine learning models to make predictions or classifications based on the data.
• Select appropriate algorithms and techniques for specific problems.
• Train, validate, and test models to ensure they perform well.
• Create visualizations to communicate findings clearly and effectively to stakeholders.
• Present complex data in a user-friendly manner.
• Apply statistical techniques to analyze data and draw meaningful conclusions.
• Conduct hypothesis testing and regression analysis.
• Ensure the statistical validity of the results.
• Collaborate with business leaders, analysts, and other stakeholders to understand their needs and requirements.
• Define project scope, goals, and deliverables. Develop detailed project plans, timelines, and resource allocations.
• Provide technical guidance and mentorship to the project team, ensuring best practices in data engineering, analytics, and AI/ML model development.
• Serve as the primary contact for client communications, ensuring clear and effective information exchange.
• Conduct Q&A sessions with senior and execution-level bankers.
• Evaluate and ensure quality control and standardization of deliverables.
• Maintain data integrity and efficient processing by monitoring and optimizing data pipelines.
• Develop PowerBI dashboards that meet client requirements and provide actionable insights.
• Translate business problems into data-driven solutions.
• Communicate findings and recommendations to non-technical stakeholders.
• Fine-tune algorithms and models to improve their performance.
• Implement feature engineering to enhance model accuracy.
• Use cross-validation and other techniques to prevent overfitting.
• Write efficient and maintainable code in languages such as Python, R, or SQL.
• Develop and maintain data pipelines and workflows.
• Monitor the performance of deployed models to ensure they continue to perform well over time.
• Update models as new data becomes available or as business needs change.
• Troubleshoot and resolve issues related to data quality or model performance.
• Establish and enforce data governance policies and standards.
• Promote a data-driven culture within the organization.