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Job Type

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Job Description

  • 5+ years of experience in data science, analytics, ML engineering, with a strong focus on building scalable solutions.
  • Hands-on experience developing, deploying, and optimizing Machine Learning models in production environments.
  • Expert proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, Scikit-learn).
  • Strong experience with ML deployment frameworks (MLflow, Kubeflow, SageMaker, Vertex AI).
  • Strong knowledge of feature engineering, model evaluation, and hyperparameter tuning for predictive modeling.
  • Experience with statistical programming (Python, R) and familiarity with Scala, Java, or C++ for performance optimization.
  • Proficiency in SQL for complex queries, data extraction, analysis, and profiling.
  • Experience with cloud platforms (AWS, GCP, Azure) and distributed data processing tools like Spark, Snowflake, or Databricks.
  • Deep understanding of classical ML algorithms (k-NN, Naïve Bayes, SVM, Decision Forests, Gradient Boosting, etc.).
  • Exposure to deep learning architectures such as CNNs, RNNs, and Transformers is a plus, with a strong understanding of their applications and optimizations being highly desirable.
  • Strong grasp of applied statistics, including probability distributions, regression analysis, statistical tests, and maximum likelihood estimation.

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