Business Analytics Engineer

At Aristocrat, We are on a mission to find the best talent potential individuals in thirst for innovation & Knowledge

Career in Aristocrat Involves remote modality and several cutting edge stipend linked corporate certification in house ;

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• Data Analysis: Analyzing large amounts of data, finding patterns, and generating insights to make informed
  

• Business Intelligence: Creating business intelligence dashboards, reports, and visualizations that enable business leaders to make data-driven
  

• Predictive Modeling: Using statistical models and machine learning techniques to forecast future trends, identify patterns and make
  

• Data Warehousing: Building and maintaining data warehousing systems that store and organize data for analytics and
  

• Data Quality Assurance: Ensuring the accuracy, completeness, and consistency of data across multiple systems and
  

• System Integration: Working with IT teams to integrate data from various sources and
  

• Communication: Presenting findings and insights to business leaders, stakeholders, and other
  

• Process Improvement: Continuously improving processes, tools, and technologies to streamline data analytics
  

• Project Management: Managing projects from start to finish, including planning, execution, and
  

• Collaboration: Collaborating with other teams such as marketing, finance, and operations to identify opportunities for data-driven
  
  

Requirements

• Data analysis: Business analytics engineers should be able to collect, organize, and analyze large datasets using tools like SQL, Python, and
  

• Statistical modeling: They should have a solid understanding of statistical concepts and be able to use predictive models to identify trends and patterns in
  

• Data visualization: The ability to present complex data in a clear and concise manner using tools like Tableau or Power BI is important for creating actionable
  

• Machine learning: Business analytics engineers should be familiar with machine learning techniques and algorithms, including supervised and unsupervised
  

• Problem-solving: They should be able to identify business problems and develop data-driven solutions to address
  

• Communication: The ability to communicate findings and recommendations to non-technical stakeholders is crucial for gaining buy-in and driving
  

• Project management: Business analytics engineers should be able to manage projects from start to finish, including scoping, planning, execution, and
  

• Business acumen: Understanding the business context, including the industry, market trends, and key performance indicators, is essential for developing effective analytics
  
  

Benefits

Extreme learning and training

Continuous growth every 3 months financially & in

Compensation based on contribution