Data scientist-Python and MATLAB

Exploratory Data Analysis (EDA):

• Perform deep analysis of complex datasets to uncover patterns, trends, and insights relevant to flight safety.

Anomaly Detection:

• Apply advanced techniques to detect anomalies in time-series and multivariate data, identifying potential safety risks.

AI/ML Model Development:

• Design and implement machine learning and deep learning models (e.g., ANN, RNN, CNN) for predictive safety analytics.

Big Data Analytics:

• Leverage big data platforms and AI/ML frameworks to support real-time, data-driven decision-making in safety-critical applications.

Custom Algorithm Development:

• Create and fine-tune algorithms tailored to domain-specific requirements with a focus on accuracy, performance, and reliability.

Programming & Deployment:

• Write efficient, maintainable code in Python and MATLAB for data processing, model training, and deployment.

Data Engineering:

• Collect, clean, and preprocess data from diverse sources to ensure the integrity and quality of inputs used in model development.

Collaboration:

• Work closely with cross-functional teams to convert analytical insights into actionable initiatives for improving flight safety.

Required Qualifications & Experience:

• Educational Background:
• Bachelor's degree in Engineering with a specialization in Data Science or a related discipline.
• Certification in Data Science (completed course or equivalent recognized program).

Professional Experience:

• Minimum 6 years of hands-on experience in data science, analytics, or machine learning.
• Proven expertise in developing AI/ML models, with strong focus on anomaly detection and predictive analytics.