Designing and implementing advanced Artificial Intelligence and Data Science solutions, defining scalable AI and Machine Learning architectures, and deploying models into production environments.
Responsibilities
Design and implement scalable AI, Machine Learning, and Data Science architectures aligned with business and technical requirements.
Develop, train, validate, optimize, and deploy Machine Learning models into production environments.
Build AI solutions leveraging both traditional Machine Learning algorithms and Large Language Models.
Define reliable data quality, validation, and control mechanisms to support AI initiatives.
Optimize model performance through advanced statistical techniques and hyperparameter tuning.
Requirements
Nice to have: End-to-end AI solutions design
Nice to have: Cloud platform exposure (AWS, Microsoft Azure, GCP)
Nice to have: MLOps practices
Nice to have: Large-scale distributed data environments (Cloudera)
Provides direction and specialist knowledge in applying the technology/application to client business, focusing on large or complex sales opportunities.
Responsibilities
Facilitation of customer product/application understanding through presentations demonstrations and benchmarks
Drive APAC wide go to market initiaities
Work with regions to define and drive their go to market initiativies, identify target accounts and drive large data platform opportunities
Support regions with tender requirements, proposal development, implementation estimates
Die Entwicklung und Optimierung moderner Analytics- und Datenmanagement-Lösungen liegt in deinen Händen – von der Konzeption bis zur Umsetzung. Du steuerst komplexe Projekte im Bereich Data & Analytics und übernimmst Verantwortung für deren Erfolg.
Responsibilities
Datenarchitekturen entwerfen
Modelle gestalten
ETL-/ELT-Prozesse implementieren
Kunden zu Best Practices in Datenintegration und Datenmanagement beraten
KI-gestützte Lösungsansätze und Automatisierungen entwickeln und bewerten
Requirements
Abgeschlossenes Studium der (Wirtschafts-)Informatik, Mathematik oder Naturwissenschaften
As a Data Platform Digital Solution Engineer (DSE), you will play a pivotal role in helping enterprises unlock the full potential of Microsoft’s cloud database and analytics stack across every stage of deployment. You will work directly with technical and business stakeholders to design secure, scalable, and resilient database and analytics architectures that support business-critical applications and Frontier AI transformation.
Responsibilities
Lead Databases & Analytics customer engagements
Drive technical sales with decision makers using demos and PoCs to influence solution design and enable production deployments
Drive technical workshop using live demos, co-create with customers whiteboarding & architecture, rapid prototyping, hands-on proofs of concept & pilots to resolve technical blockers
Prove technical solutions, co-create or re-use existing architecture to influence solution design and enable customer commitment for deployments
Maintain deep expertise in Analytics Portfolio: Microsoft Fabric including OneLake, Azure Databricks, and Azure Databases: SQL DB, Cosmos DB, PostgreSQL
Requirements
Bachelor's Degree in Computer Science, Information Technology, or related field
Master's Degree in Computer Science, Information Technology, or related field
Nice to have: Cloud and hybrid or on premises infrastructure architecture designs
Develop, implement, and optimise data models and algorithms to address business problems and improve decision-making.
Perform data mining, statistical analysis, and predictive modelling to identify trends, patterns, and actionable insights.
Design, develop, and deploy machine learning models using algorithms such as K-Nearest Neighbours, Naïve Bayes, Support Vector Machines, Decision Trees, and Random Forest.
Apply statistical and analytical methodologies, including hypothesis testing, experimental design, and data validation.
Use data science tools and programming languages, with hands‑on proficiency in Python or R.
Requirements
Bachelor's degree in Engineering, Computer Science, or a related discipline
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