Data Scientist

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Core Responsibilities

• Data Preparation: Collect, clean, validate, and preprocess structured and unstructured data.
• Model Development: Build machine learning algorithms, predictive models, and statistical experiments.
• Deployment & Testing: Implement models into production systems and monitor performance.
• Collaboration & Communication: Work with product managers, software engineers, and data engineers, while presenting findings via data visualizations. [1, 2, 3, 4, 5]
  

Required Skills & Qualifications

• Education: Bachelor's or Master’s degree in a quantitative field such as Computer Science, Statistics, Applied Mathematics, or Engineering. [1, 2]
• Programming Languages: Proficiency in Python or R, alongside SQL for database querying. [1, 2]
• Technical Tools: Experience with machine learning libraries, big data frameworks (such as Hadoop or Spark), and data visualization tools (such as Tableau or Power BI). [1, 2]
• Core Competencies: Strong foundation in statistics, pattern recognition, data mining, and translating data into actionable business strategies. [1, 2]