Contract Specialist

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

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

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• Collect, clean, and preprocess large datasets from various sources to develop predictive models.
  
• Analyze and interpret data to identify patterns, relationships, and trends.
  
• Select appropriate algorithms, techniques, and tools to build predictive models that meet business needs.
  
• Build, validate, and test predictive models to ensure accuracy and reliability.
  
• Collaborate with cross-functional teams to integrate models into business processes and decision-making.
  
• Communicate findings, insights, and recommendations to stakeholders in a clear and concise manner.
  
• Develop and maintain documentation of the modeling process, assumptions, and limitations.
  
• Keep up-to-date with industry trends and advancements in predictive modeling techniques.
  
• Ensure compliance with regulatory and ethical standards for modeling and data privacy.
  

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Requirements

• Bachelors or Masters degree in Mathematics, Statistics, Computer Science, or a related field.
  
• 1+ years of experience in predictive modeling, with a proven track record of designing and implementing successful models.
  
• Strong analytical and problem-solving skills.
  
• Proficiency in statistical analysis software and programming languages such as R or Python.
  
• Experience with machine learning algorithms, decision trees, neural networks, and time series analysis.
  
• Excellent communication and presentation skills to convey complex information to stakeholders.
  
• Ability to work in a fast-paced environment and handle multiple projects simultaneously.
  
• Knowledge of industry-specific regulations and ethical standards related to modeling and data privacy.
  

Benefits

Extreme Learning and training environment.

Continuous growth every 3 months financially & in Responsibilities.

Compensation based on contribution value.