
Data Science Specialist
3 days ago
We are searching for a skilled professional to work on cutting-edge AI/ML projects, collaborating with senior engineers to design, develop, and deploy innovative solutions.
Key Tasks:
- Data Transformation: Convert raw data into a suitable format for machine learning modeling, ensuring high-quality data for optimal model performance.
- Model Refining: Collaborate with senior engineers to refine machine learning models for improved accuracy, efficiency, and scalability.
- Model Improvement: Participate in the improvement and fine-tuning of models to enhance their performance and adapt them to real-world scenarios.
- Research and Development: Conduct research on new and emerging AI/ML techniques and contribute to proof-of-concept development, exploring innovative applications and solutions.
- Documenting Progress: Document model development, research, and performance metrics for future reference and learning, promoting knowledge sharing within the team.
- Cross-Functional Teamwork: Collaborate with cross-functional teams to understand business problems and provide AI/ML-driven solutions that meet the company's needs.
- Pipeline Creation: Assist in creating deployment pipelines for ML models, ensuring they are scalable, efficient, and well-integrated into the overall system.
- Implementation: Assist in the development and implementation of machine learning models for various business applications, focusing on practical and effective solutions.
Requirements:
- Mathematical Background: Strong foundation in mathematics, statistics, and computer science is required.
- Programming Expertise: Familiarity with Python and popular libraries like TensorFlow, Keras, PyTorch, or scikit-learn, with a focus on efficient and effective coding practices.
- Data Understanding: Basic knowledge of data preprocessing, data manipulation, feature engineering, statistics, probability distributions, hypothesis testing, linear algebra, and calculus for a deep understanding of ML models.
- Database Knowledge: Knowledge of SQL for data querying and experience handling large datasets.
- Version Control: Familiarity with version control using Git, ensuring smooth collaboration and code management.
- Soft Skills: Strong problem-solving skills, excellent teamwork abilities, and a keen interest in developing AI-driven solutions that drive business results.
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