• Collaborate with stakeholders to understand business challenges and develop data-driven solutions.
  
• Build, deploy, and refine machine learning models for tasks such as predictive analysis, classification, and clustering.
  
• Conduct exploratory data analysis and feature engineering to uncover meaningful insights from large datasets.
  
• Apply advanced statistical methods and machine learning algorithms to create effective data models.
  
• Create compelling data visualizations, reports, dashboards, and presentations to communicate insights and recommendations.
  
• Stay current with the latest data science technologies, trends, and best practices.

Requirements

• Bachelor’s or Master’s degree in Data Science, Statistics, Applied Mathematics, or a related field.
  
• Proficiency in Python and R for data analysis and machine learning tasks.
  
• Strong knowledge of machine learning algorithms (e.g., regression, clustering, decision trees, deep learning).
  
• Experience using data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn.
  
• Hands-on experience with machine learning frameworks like Tensor Flow, Py Torch, or Scikit-learn.
  
• Understanding of A/B testing, hypothesis testing, and other statistical analysis methods.
  
• Experience in deploying and maintaining machine learning models.
  

• Experience working with big data platforms (e.g., Hadoop, Spark) or cloud platforms (e.g., AWS, Google Cloud).
  
• Experience with SQL for database management and querying.
  
• Familiarity with data engineering tools and techniques.

Benefits

• Competitive salary and career growth opportunities.
  
• Flexible working hours with the option to work remotely.
  
• Be part of a collaborative and forward-thinking team.
  
• Opportunity to influence business decisions through data-driven insights in a rapidly growing industry.