Python programmer állások, munkák it programozás, fejlesztés területen

• Development, governance, deployment, and ongoing enhancement of liquidity analytics models and supporting infrastructure across asset classes
• Driving the analytics product lifecycle, including prioritizing initiatives, influencing roadmap decisions, and ensuring successful deployment into production

• Ownership of product vision, strategy, and roadmap for the Omnichannel analytics suite
• Definition of the problem space including business outcomes, user needs, scope, and product backlog
• Management of the full APEX product lifecycle across Omnichannel initiatives

• Lead implementation of AI, GenAI, ML, automation, and AI-powered applications.
• Translate solution designs and requirements into development plans and working software.
• Drive engineering delivery aligned with the target architecture.

• AI-eszközök bevezetésében, integrációjában és üzleti környezetbe történő beágyazásában való aktív közreműködés
• Üzleti igények feltérképezése, valamint AI use case-ek üzleti és technológiai megvalósíthatóságának értékelése

• Shape and implement the company’s data science strategy and drive innovation, with a primary focus on Generative AI and Agentic workflows
• Identify opportunities to leverage data for business value and impact
• Take ownership of the full technical stack for development and deployment

• The CloudOps Engineer is responsible for availability for cloud platforms
• Respond, troubleshoot and resolve production alarms
• Communicate and troubleshoot operational issues supporting a complex environment
• Respond to cloud service outages and manage incident tickets

• Vállalati szintű adatfeldolgozó (ETL/ELT) folyamatok tervezése és megvalósítása
• Adatintegrációs megoldások fejlesztése heterogén rendszerek között
• Adatmodellek kialakítása, optimalizálása és dokumentálása
• Adatminőségi kontrollok és monitoring mechanizmusok implementálása

• Discovery & Shaping: Lead stakeholder workshops, translate business needs into MVP scopes, and map out scalable implementation roadmaps.
• End-to-End Architecture: Design and document (C4 diagrams, API contracts) robust cloud architectures covering application, data, and LLM layers.

• statisztikai és gépi tanulási modellek fejlesztése, karbantartása és monitorozása
• piackutatások készítése
• adatvezérelt megoldások kidolgozása az értékesítés, kárrendezés, ügyfélkiszolgálás és termékterületek támogatására

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Design and configuration of data labeling and processing pipelines using Python-based tools

• collaborating on the design and development of ML‑based applications and their backend components
• helping to select the most applicable solutions for a given business problem
• writing clean, efficient and well‑documented code
• contributing to our MLOps processes

• Creation and preparation of 3D assets, environments, and scene layouts for Omniverse and OpenUSD workflows
• Assembly of digital-twin scenes for industrial, facility, product, or enterprise visualization use cases

• Definition and improvement of metrics reflecting product performance, service quality, and operational efficiency
• Analysis of client behavior and service processes to identify trends, bottlenecks, inefficiencies, and drivers of performance

• Development and deployment of AI-powered applications from prototype to production using modern LLM frameworks and APIs
• Design of evals and metrics measuring real-world performance including accuracy, latency, UX quality, and safety

nemzetközi környezetben dolgozni, ahol az Erste Csoport 8 országának modellezési csapataival együttműködve fejlesztjük a kockázatkezelési modelleket és módszertanokat...

• Define and execute test strategies across the full stack: backend APIs (FastAPI), frontend UIs, and agentic workflows.
• Define testing standards and frameworks that enable developers to own unit and integration test coverage, in line with a shift-left quality model.

• Support the application and automation of quantitative techniques used to assess investment managers across various asset classes
• Assist with maintaining and updating data processes and analytical tools used in manager and portfolio analysis

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives

• Managing complex database systems within a global technology ecosystem
• Building and managing database hosting capabilities using Infrastructure as Code for all platform needs
• Building database infrastructure platforms with developers and providing guidance and tooling to handle distributed systems

• Managing day-to-day operations of Databricks data pipelines, including monitoring, troubleshooting, and performance tuning
• Maintaining Delta Lake data layers (bronze / silver / gold), ensuring data availability, consistency, and smooth pipeline execution