Data science állások, munkák it programozás, fejlesztés területen

• Co-design and implement QA workflows using statistical diagnostics, validation rules, and anomaly detection techniques
• Application of AI/machine learning tools to identify inconsistencies, missing values, or suspicious patterns in large-scale asset datasets

• 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

• Design and build backend services and APIs supporting data ingestion, transformation, and delivery to frontend and downstream consumers
• Own data storage and pipeline architecture including integration with streaming/event infrastructure

Assess and document downstream impact of Skills and Job Architecture data quality issues across payroll processing, management reporting, third-party integrations, and AI/machine learning model inputs...

• Definition and improvement of metrics representing product performance and operations efficiency
• Data collection from multiple sources ensuring accuracy and completeness
• Data cleaning, organization, and transformation into usable formats for analysis

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• Trade a wide range of financial instruments
• Develop, maintain, and improve trading strategies and algorithms
• Run trading desks and support day-to-day trading operations
• Manage execution and risk across complex trading portfolios
• Analyze market data and identify opportunities for strategy improvement

• Owning a revenue target across data, advanced analytics, and predictive AI
• Leading executive-level client conversations, joining deals early to diagnose the business problem, structure a solution, and build the ROI case that gets the client to sign

• Design, build, and deploy production-grade agentic AI and automation solutions that collect, validate, and quality-assure data at scale
• Engineer multi-agent orchestrations, data pipelines, MCP integrations, and API connections that power autonomous, end-to-end data workflows

• Geographic information systems, spatial analysis, and map server infrastructure
• Maintain a performance oriented GeoServer and database
• Create new features based on specification
• Actively take part in the system design
• Optimize data flows, build automated data piplines

• Design, develop, and maintain high-quality C++ software components and services.
• Build and integrate scalable APIs, database solutions, and data-processing pipelines.
• Collaborate with data scientists and operations research specialists to bring models into production and industrialize their code.

• 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.

• 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.

Ready to fast‑track your career and take on real global challenges? ...

• Geographic information systems, spatial analysis, and map server infrastructure
• Maintain a performance oriented GeoServer and database
• Create new features based on specification
• Actively take part in the system design
• Optimize data flows, build automated data piplines

• 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

• 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

• Collaboration with senior product managers to ensure achievement of product objectives
• Support of key projects within the product management team
• Collaboration with research, engineers and program management teams

• Lead annual and periodic User Developed Application (UDA) assessments and certifications, ensuring compliance with bp controls and regulatory requirements
• Partner with participants, application owners and technical teams to identify, assess and remediate control gaps, reducing risk

• Consultant and technical expert on the Salesforce platform providing support to stakeholders and users
• Collaboration with experts from other areas to leverage Salesforce technologies through integrations