
Data Scientist
1 week ago
- The ideal candidate will have a strong background in AI/ML, with hands-on experience in developing data-driven solutions
- You will collaborate with cross-functional teams to build and deploy machine learning models that solve real-world problems, improve business processes, and drive decision-making
- Key Responsibilities: Develop machine learning models and algorithms to extract insights and make data-driven decisions
- Implement advanced data analytics and machine learning models using AI/ML techniques
- Work closely with product and business teams to understand business requirements and translate them into machine learning solutions
- Collaborate with data engineers to collect, clean, and process large datasets
- Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies in data
- Design and implement data pipelines to automate the processing and analysis of data
- Test and validate models to ensure they perform optimally in production
- Optimize existing models for improved performance and scalability
- Communicate results to non-technical stakeholders through clear visualizations and reports
- Stay up-to-date with the latest developments in the field of AI/ML
- Required Skills and Qualifications: 4-7 years of experience in Data Science, with a minimum of 3 years in AI/ML development
- Proficiency in programming languages such as Python and R for building machine learning models
- Strong understanding of machine learning algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning
- Hands-on experience with AI/ML frameworks such as TensorFlow, Keras, PyTorch, or Scikit-learn
- Experience with data wrangling, feature engineering, and model evaluation techniques
- Familiarity with data visualization tools such as Matplotlib, Seaborn, or Tableau
- Strong knowledge of SQL for querying large datasets
- Familiarity with cloud platforms (eg) AWS, Azure, GCP) and tools for model deployment and scaling
- Experience with Docker and Kubernetes for model deployment is a plus
- Excellent problem-solving skills and ability to work in a fast-paced environment
- Strong communication skills to present technical concepts to non-technical stakeholders
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