Automation and Analytics Specialist

As an Automation and Analytics Specialist, you will be responsible for developing automated processes and utilizing data analytics and data science to enhance business operations. Your key responsibilities will include: - Data Collection and Analysis: - Gather data from various sources such as databases and APIs. - Clean, transform, and prepare data for analysis. - Perform exploratory data analysis (EDA) to uncover patterns and insights. - Develop reports and visualizations to effectively communicate findings. - Automation Development: - Identify and implement process enhancements through automation. - Create and maintain automated business processes, including reporting and forecasting tools. - Utilize automation tools like Python scripting, RPA, or other suitable technologies. - Data Modeling and Analytics: - Build and test statistical models for data analysis and predictions. - Utilize techniques such as AI, ML, Gen AI, and agentic AI to develop relevant business solutions. - Establish and maintain data pipelines for efficient data processing. - Offer insights and recommendations based on data analysis. - Collaboration and Communication: - Collaborate with stakeholders to comprehend data requirements and provide technical solutions. - Communicate findings and recommendations to both technical and non-technical audiences. Essential Qualifications: - Bachelor's degree in a relevant field (e.g., statistics, data science, computer science, engineering), or equivalent experience. - Minimum 5 years of experience in delivering projects using automation, analytics, and data science techniques. - Proficiency in programming languages like Python or SQL. - Strong analytical skills and experience with data analysis techniques. - Ability to create clear and insightful data visualizations. - Understanding of automation concepts and experience with relevant tools. - Problem-solving skills using data and analytical techniques. Desired Skills: - Experience with AI, ML algorithms and techniques, Gen AI, agentic AI. - Previous exposure to data warehousing technologies and platforms. - Understanding of business processes and leveraging data for decision-making. As an Automation and Analytics Specialist, you will be responsible for developing automated processes and utilizing data analytics and data science to enhance business operations. Your key responsibilities will include: - Data Collection and Analysis: - Gather data from various sources such as databases and APIs. - Clean, transform, and prepare data for analysis. - Perform exploratory data analysis (EDA) to uncover patterns and insights. - Develop reports and visualizations to effectively communicate findings. - Automation Development: - Identify and implement process enhancements through automation. - Create and maintain automated business processes, including reporting and forecasting tools. - Utilize automation tools like Python scripting, RPA, or other suitable technologies. - Data Modeling and Analytics: - Build and test statistical models for data analysis and predictions. - Utilize techniques such as AI, ML, Gen AI, and agentic AI to develop relevant business solutions. - Establish and maintain data pipelines for efficient data processing. - Offer insights and recommendations based on data analysis. - Collaboration and Communication: - Collaborate with stakeholders to comprehend data requirements and provide technical solutions. - Communicate findings and recommendations to both technical and non-technical audiences. Essential Qualifications: - Bachelor's degree in a relevant field (e.g., statistics, data science, computer science, engineering), or equivalent experience. - Minimum 5 years of experience in delivering projects using automation, analytics, and data science techniques. - Proficiency in programming languages like Python or SQL. - Strong analytical skills and experience with data analysis techniques. - Ability to create clear and insightful data visualizations. - Understanding of automation concepts and experience with relevant tools. - Problem-solving skills using data and analytical techniques. Desired Skills: - Experience with AI, ML algorithms and techniques, Gen AI, agentic AI. - Previous exposure to data warehousing technologies and platforms. - Understanding of business processes and leveraging data for decision-making.