Python Engineer

Summary:

• Work Mode: Not specified

Responsibilities:

• Design, develop, test, and support Python-based applications and analytical solutions.
• Perform data extraction, cleansing, transformation, and analysis from structured and unstructured data sources.
• Develop and enhance predictive and prescriptive models using statistical, machine learning, and AI techniques.
• Support implementation of machine learning solutions in development and production environments.
• Apply object-oriented programming principles and established engineering standards to deliver high-quality solutions.
• Collaborate with business, technology, and data teams to understand requirements and develop appropriate solutions.
• Contribute to application design, coding, testing, debugging, and deployment activities.
• Participate in model development, monitoring, and performance evaluation processes.
• Utilize Python, SQL, and related technologies to develop scalable analytical solutions.
• Develop and maintain scripts and automation solutions using Linux and shell scripting.
• Implement unit testing and support test-driven development practices.
• Document technical solutions, methodologies, and processes.
• Stay current with emerging technologies, including ML, DL, LLMs, and GenAI.
• Adhere to technology risk, security, compliance, and control requirements.

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• Minimum 2 years of experience in software engineering, data science, machine learning, or advanced analytics.
• Experience developing applications and analytical solutions using Python.
• Familiarity with machine learning concepts, model development, and AI technologies.
• Proficiency in Python, SQL, Spark, PySpark, TensorFlow, or similar technologies.
• Familiarity with Linux environments and shell scripting.
• Strong analytical and problem-solving skills.
• Ability to work independently and collaboratively within a team environment.
• Strong verbal and written communication skills.

Preferred Skills:

• Exposure to GenAI and LLM-based solutions.
• Experience with distributed computing technologies such as Hadoop, Hive, Spark, or similar platforms.
• Experience in banking, financial services, or risk management environments.
• Familiarity with credit risk, capital markets, financial instruments, or quantitative modeling.
• Understanding of software development lifecycle (SDLC), CI/CD, and cloud-based development environments.