Senior Data Scientist Specialist

2 days ago

Delhi Delhi NCR, India beBeeData Full time US$ 90,000 - US$ 1,20,000
Machine Learning Engineer

We're seeking a seasoned Machine Learning Engineer to join our innovative team.

Key Responsibilities:

  • Data Analysis & Feature Engineering: Conduct comprehensive data analysis, feature engineering, and exploration to extract valuable insights from diverse datasets.
  • Model Development & Optimization: Develop and optimize cutting-edge Machine Learning models to achieve high accuracy, efficiency, and performance.
  • Deep Learning Implementation: Design and implement advanced Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques.
  • Imbalanced Data Handling: Effectively handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness, generalization, and robustness.
  • Model Deployment & Monitoring: Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on real-world feedback and performance metrics.
  • Cross-Functional Collaboration: Collaborate seamlessly with cross-functional teams, including data scientists, software engineers, and product managers, to align ML solutions with overarching business goals.
  • Statistical & Mathematical Application: Utilize fundamental statistical knowledge and strong mathematical principles to ensure the reliability, validity, and interpretability of models.
  • Innovation & Research: Stay abreast of the latest advancements in ML and AI, actively bringing in new techniques and research findings to drive innovation within the team and company.

Requirements:

  • Hands-on experience in Machine Learning and Deep Learning.
  • Strong expertise in feature engineering, data exploration, and data preprocessing.
  • Experience with imbalanced datasets and techniques to improve model generalization.
  • Proficiency in Python, TensorFlow, Scikit-learn, and other relevant ML frameworks and libraries.
  • Strong mathematical and statistical knowledge coupled with excellent problem-solving skills.
  • Ability to optimize models for high accuracy and performance in real-world scenarios.

Preferred Qualifications:

  • Experience with Big Data technologies (e.g., Hadoop, Spark).
  • Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
  • Experience in automating ML pipelines with MLOps practices.
  • Experience in model deployment using cloud platforms (e.g., AWS, GCP, Azure) or MLOps tools.

Benefits:

  • Opportunity to work with cutting-edge technologies and innovative projects.
  • Collaborative and dynamic work environment.
  • Professional growth and development opportunities.

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