Analyze large and complex datasets to discover trends, patterns, and insights. Apply statistical methods and machine learning techniques to extract valuable information from data.
Develop and implement machine learning algorithms and models for predictive and prescriptive analysis. Utilize deep learning techniques for complex data analysis tasks.
Utilize Python programming language and libraries such as numpy and pandas to manipulate data, conduct analysis, and develop machine learning models.
Create compelling data visualizations using tools such as Matplotlib, Seaborn, or Tableau to communicate complex findings effectively. Present data-driven insights to stakeholders.
Identify relevant features and perform feature engineering to enhance the performance of machine learning models.
Evaluate the performance of machine learning models using appropriate metrics. Fine-tune models for optimal results.
Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to understand business requirements and provide data-driven solutions.
Maintain detailed documentation of data analysis processes, algorithms, and models. Ensure that documentation is clear, concise, and accessible to relevant team members.
What you’ll need:
3 years as AI Engineer with expertise in Python, deep learning, algorithms, numpy, and data visualization tools.
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
Proficiency in Python programming and libraries such as numpy, pandas, and scikit-learn.
Experience with deep learning frameworks such as TensorFlow or PyTorch.
Strong SQL skills
Strong mathematical and analytical skills.
Excellent problem-solving abilities and attention to detail.