Senior Python Developer(3+years)

VR-123944 Project description Our customer is a top-tier investment bank with client assets of hundreds of billions globally. Reason to join us • We offer the opportunity to work in a highly professional environment where you will work with high-level financial instruments • We want you to be part of our success story and give you reasons to be proud of what you achieved as part of our fabulous team • We give you the opportunity to develop yourself and evolve in your career via our fantastic technical, business-related or soft skills training • We encourage creative-thinking in our great open-minded work environment. Frequently the relaxation rooms are the place where the most ambitions ideas are born. • We are not just professional teams, we are also friends that have fun working together • If you are an active person and you feel motivated by the creation/development of the software solutions, then this is the place to be, you will not get bored. Responsibilities Collaborate with global stakeholders to understand business requirements and translate them into scalable, production-ready AI solutions. Design and build data transformation frameworks, manage data ingestion pipelines, and support AI/ML-driven processes. Deploy machine learning models as production-grade APIs, microservices, and software applications, ensuring scalability, reliability, and ongoing performance monitoring. Build, maintain, and optimize the technology infrastructure required for AI development, including cloud platforms (AWS, GCP, Azure) and containerized environments. Develop and implement algorithms for personalization, anomaly detection, and intelligent automation while ensuring compliance with regulatory and governance standards. Partner closely with data scientists, software engineers, product managers, and business stakeholders to define AI strategies and deliver innovative features. Maintain comprehensive documentation of AI processes, controls, standards, and technical solutions in accordance with the Bank's data governance framework. Actively participate in Agile ceremonies, including sprint planning, backlog refinement, and iterative delivery activities. Stay informed on emerging AI technologies, including Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures, identifying opportunities to create business value through their adoption. Develop, optimize, and support scalable AI and Machine Learning models throughout their lifecycle. Build robust Extract, Transform, and Load (ETL) processes for handling large volumes of real-time and unstructured data used in AI/ML solutions. Conduct experiments and performance testing of deployed models, identifying, troubleshooting, and resolving issues to ensure model effectiveness and reliability. Apply expertise in statistics, programming, and scripting languages within a collaborative, team-oriented environment. Work with the software platforms and deployment environments that host AI and ML solutions, ensuring operational excellence and continuous improvement. Skills Bachelor's or Master's degree in Artificial Intelligence, Data Science, Computer Science, Information Technology, Software Engineering, Computer Studies, or a related discipline. Advanced proficiency in Python, including modern language features, industry-standard libraries (e.g., Scikit-Learn, NumPy, Pandas), Object-Oriented Programming (OOP), S.O.L.I.D. principles, and data structures and algorithms with a strong understanding of performance optimization. Strong understanding of software engineering fundamentals, including operating systems, programming and query languages (e.g., Java, SQL), version control systems (Git), software development methodologies (Agile, Waterfall), CI/CD practices (e.g., Jenkins), software testing, monitoring, and observability. Foundational knowledge of software architecture, design patterns, and cloud computing technologies, including AWS, GCP, and Azure. Practical experience in the theoretical and applied aspects of Machine Learning, including model development, evaluation, deployment, and maintenance. Ability to perform code reviews, promote development best practices, and contribute to overall code quality within the team. Strong expertise across the end-to-end data lifecycle, including data engineering, cloud and traditional database technologies, data modeling, query optimization, data preprocessing, feature engineering, and data transformation. Excellent communication and storytelling skills, with the ability to present complex technical concepts and analytical findings clearly to technical and non-technical audiences, including senior stakeholders. Experience creating data visualizations and dashboards using tools such as Tableau or similar platforms to support business decision-making. Strong analytical thinking, problem-solving capabilities, and attention to detail. Excellent written and verbal communication skills. Proven ability to work independently as well as collaboratively within global, cross-functional teams. Familiarity with Agile delivery methodologies, user story creation, and requirements documentation.