Machine Learning Analyst

Job Summary

• The Machine Learning Analyst is responsible for developing and implementing machine learning models to analyze and interpret complex data sets. The role collaborates with cross-functional teams to identify business needs, design algorithms, and extract valuable insight from data. The role may also be involved in data pre-processing, feature engineering, and model evaluation to ensure the effectiveness of machine learning solutions.

Job Responsibilities 1

• Build and optimize web applications from the front end to the back end.
• Integrate user-facing elements using server-side logic and connecting the application with the cloud infrastructure.
• Design and implement databases to store and retrieve data efficiently.
• Optimize database performance and ensure data integrity.
• Develop data pipelines for ETL (Extract, Transform, Load) processes.
• Design, develop, and implement machine learning models to solve specific business problems using algorithms suitable for the task.
• Identify and select relevant features or variables that contribute to the performance of machine learning models.
• Analyze and understand large data sets to identify patterns, trends, and insights relevant to business goals.
• Clean and prepare raw data for analysis, ensuring data quality and handling missing and inconsistent information.
• Integrate and process data from various sources to support business needs.
• Implement security measures for cloud-based solutions, including access controls, encryption, and compliance with industry standards. Monitor and optimize the performance of cloud-based applications and infrastructure.

Job Responsibilities 2

Identify and address bottlenecks to ensure optimal system performance.

Collaborate with cross-functional teams, including other developers, data scientists, and system administrators.

Communicate technical concepts effectively to non-technical stakeholders.

Adhere to agile development methodologies and participate in sprint planning, reviews, and retrospectives.

Develop and maintain database architectures using MSSQL.

Collaborate with stakeholders to gather and comprehend business requirements for data collection and analysis.

Perform data validation to ensure accuracy, completeness, and consistency of data.

Analyze data sets, generate insights, and create reports using Power BI or similar tools.