🏢 Company Overview:
Amazon is a global leader in e-commerce, cloud computing, and AI-driven solutions. The company focuses on leveraging data and technology to deliver innovative services and experiences to millions of customers worldwide. Amazon provides a collaborative and growth-oriented environment for data professionals to work on high-impact projects.
💼 Job Details:
- Employment type: Full Time
- Experience: 9 Years
- Salary: 9.2L to 11L Yearly
- Location: Work For Home
- Work timing: 9:45 AM to 6:45 PM
- Working Days: 5 Days
- Education: Any Degree
📝 Job Description:
Amazon is seeking a Data Scientist proficient in Python to analyze large datasets, build predictive models, and generate actionable insights. The ideal candidate will collaborate with cross-functional teams to solve complex business problems, optimize processes, and support data-driven decision-making.
🔑 Key Responsibilities:
- Analyze large and complex datasets using Python and statistical techniques
- Develop predictive and machine learning models to support business goals
- Create visualizations and dashboards to communicate insights effectively
- Collaborate with engineers, analysts, and stakeholders to define data requirements
- Optimize data pipelines and workflows for performance and scalability
- Conduct experiments and A/B testing to validate models and strategies
🛠️ Required Skills & Qualifications:
- Strong proficiency in Python and relevant libraries (Pandas, NumPy, scikit-learn, etc.)
- Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly
- Knowledge of SQL and database management
- Understanding of machine learning algorithms and statistical modeling
- Strong problem-solving, analytical, and communication skills
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field
🌟 Benefits:
- Work on high-impact global projects with cutting-edge technologies
- Flexible work arrangements including remote and hybrid options
- Opportunities for professional growth and continuous learning
- Collaborative, innovative, and supportive work environment
