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AmpsTek - Data Scientist - Neural Networks

AmpsTek - Data Scientist - Neural Networks

AmpstekDelhi, IN
28 days ago
Job type
  • Remote
Job description

Role : Data Scientist.

Key Responsibilities :

  • Develop and implement advanced data science models, including clustering, segmentation, random forest, gradient boosting (e.g. , XGBoost), ensemble techniques, and constrained optimization methods.
  • Explore additional approaches such as neural networks, support vector machines, and Bayesian methods to address diverse business challenges.
  • Design and execute matched-pair analyses, predictive analytics, and other statistical approaches to address business challenges.
  • Collaborate with stakeholders to identify use cases for advanced modeling and provide data science-driven solutions.
  • Engineer features and preprocess data to optimize model performance and interpretability.
  • Work with large datasets from diverse sources, ensuring data quality and consistency.
  • Perform model evaluation, tuning, and validation using appropriate techniques and metrics.
  • Deploy machine learning models into production environments, ensuring scalability and reliability.
  • Mentor and collaborate with team members to share knowledge and best practices.
  • Stay current on advancements in data science, tools, and methodologies to bring innovation to the team.

Qualifications :

  • 4-8 years of work experience in classification, regression, clustering, association, dimension reduction, natural language processing (NLP), experiments, and optimization.
  • Proficiency in Python or R, with strong experience in libraries such as scikit-learn, TensorFlow, PyTorch, or similar.
  • Advanced knowledge of machine learning algorithms, statistical modeling, and data preprocessing techniques.
  • Strong foundation in mathematics, statistics, and computer science.
  • Proficiency in SQL for data extraction and manipulation.
  • Demonstrated ability to handle complex datasets and derive actionable insights.
  • Excellent communication and collaboration skills to work with cross-functional teams.
  • Experience deploying models into production environments is highly desirable.
  • ref : hirist.tech)

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