🌟 Programming Languages

• Python: Advanced proficiency with experience in data analysis, machine learning, and scientific computing.
• C++: Strong background in systems programming and algorithmic problem-solving.
• Fortran: Specialized knowledge, particularly in numerical simulations and high-performance computing.
• R: Experienced in statistical modeling and data visualization.
• MATLAB: Versatile user with focus on engineering and scientific applications.

🛠 Machine Learning Frameworks

• Scikit-learn: In-depth experience with predictive data analytics, feature extraction, and model evaluation.
• TensorFlow: Skilled in building and deploying neural network models for diverse tasks.
• PyTorch: Accomplished in designing complex architectures for both supervised and unsupervised learning.

📊 Database Management

• MySQL: Proficient in relational database design, query optimization, and data manipulation.

🔍 Quantitative Abilities

• Probability: Robust understanding of probabilistic models and statistical inference.
• Statistics: Strong grasp of statistical methods including hypothesis testing, regression, and Bayesian inference.
• Advanced Calculus: Proficient in mathematical modeling and differential equations.

🤔 Analytical Skills

• Problem-solving: Exceptional skills in approaching complex problems, devising effective solutions, and driving issues to resolution.
• Analytical Thinking: Capable of dissecting complex systems and data sets to extract insights and make informed decisions.