Senior Data Insight Professional

2 weeks ago

Malappuram, Kerala, India beBeeData Full time ₹ 18,00,000 - ₹ 25,00,000
Key Role: Senior Data Scientist

This is a pivotal position for a Senior Data Scientist who will play a crucial role in driving business decision-making through actionable insights derived from structured and unstructured data.

The ideal candidate will possess 3 to 5 years of experience in data analytics and machine learning, with hands-on expertise in ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.

They should be proficient in writing production-quality code in Python, with a strong understanding of object-oriented programming principles and proven experience in analyzing and working with large datasets.

The Senior Data Scientist will be responsible for conducting end-to-end machine learning and data analytics activities, including data wrangling, feature engineering, building and evaluating ML models.

They will research and implement novel machine learning approaches to enable informed business decisions.

Collaboration with business and engineering teams is essential, as the Senior Data Scientist will analyze, extract, normalize, and label relevant data.

Data engineering, feature engineering, data preprocessing to train and tune ML models, and utilizing Business Intelligence tools to prepare reports, analyze and visualize data are also key responsibilities.

Implementing MLOps practices such as Continuous Integration/Continuous Deployment (CI/CD) and continuous training (CT) for deploying and maintaining ML models in production environments is critical.

Responsibilities:

  • Derive actionable insights from structured and unstructured data to support business decision-making
  • Conduct end-to-end machine learning and data analytics activities
  • Research and implement novel machine learning approaches
  • Analyze, extract, normalize, and label relevant data
  • Utilize Business Intelligence tools to prepare reports, analyze and visualize data
  • Implement MLOps practices

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