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Data Scientist



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5-7 Years
2 months ago
131 Viewed
8 Applied

Job Description


Able to adapt to changing project conditions.

Collaborate with stakeholders to understand business requirements and identify opportunities for leveraging AI/ML solutions.

Design, develop, and deploy machine learning models and AI-driven applications using Python and libraries such as TensorFlow, PyTorch, scikit-learn, etc.

Gather, preprocess, and analyze data from various sources to build robust datasets for training and evaluation of machine learning models.

Experiment with different algorithms and techniques to improve model performance, accuracy, and efficiency.

Work closely with cloud platform teams to deploy and integrate machine learning models into cloud-based applications using Azure Machine Learning or AWS SageMaker.

Implement monitoring and logging mechanisms to track model performance and detect anomalies in real-time.

Collaborate with cross-functional teams including data scientists, software engineers, and business analysts to drive AI/ML initiatives.

Stay updated with the latest trends and developments in AI/ML technologies, cloud platforms, and best practices.

Document design decisions, algorithms, and procedures for model development, deployment, and maintenance.

Experience in Azure or AWS cloud Services.

Integrate third-party APIs and services to extend application functionality.

Implement best practices for code quality, performance, security, and maintainability.

Experience with Git or other version control systems.

Troubleshoot and debug issues, perform root cause analysis, and implement solutions in a timely manner.

Participating in daily scrum meetings.

Be able to work as an individual and as part of a team.

Be able to work to tight deadlines.

Required Experience

Must Have:

5+ years of experience in developing and deploying machine learning models and AI-driven applications.

Experience in Supervised Learning Models, Unsupervised Learning Models, Reinforcement Learning Models, Natural Language Processing (NLP) Models, Computer Vision Models

  • understanding of machine learning algorithms, deep learning techniques, and statistical modeling.
  • proficiency in Python and its ecosystem (libraries, frameworks, etc.).
  • of data preprocessing, feature engineering, and data visualization techniques.
  • with Python frameworks (e.g. Django, Flask, Bottle)
  • of databases and SQL
  • SQL MongoDB, Document DB
  • with cloud platforms such as Azure or AWS.
  • with cloud services such as Azure App Service, AWS Lambda, Azure Functions, AWS EC2, Azure SQL Database, AWS S3, etc.
  • 4 projects should have worked in AI/ML.

Good to Have:

Experience with big data technologies such as Apache Spark, Hadoop, Power BI, Prompt Engineering and GenAI


Experience in Python libraries like NumPy, Pandas, SciPy, Matplotlib, TensorFlow, PyTorch, scikit-learn, Flask, Django are widely used in scientific computing.

Experience in Azure Services like Azure SQL, Azure App Service, Azure Storage and Azure Function APP


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