Über Nasiba
Englisch
Muttersprachlich oder zweisprachig
Deutsch
Verhandlungssicher
Projekt- und Berufserfahrung
- FreelanceData Science & AI Engineering ConsultantBANKEN & VERSICHERUNGENOktober 2025 - Heute (10 Monate)Düsseldorf, DeutschlandDesigned and deployed an LLM-powered backend service (RAG) for a European bank, enabling semantic search and analysis over financial documents.Built production-ready pipelines including data ingestion, chunking, embedding generation, vector search.Implemented agent-like workflows and orchestration logic using LangGraph state machine model for multi-step document retrieval and reasoning.Served RAG pipeline via Databricks Model Serving endpoints, integrating with downstream banking applications through job-orchestrated inference workflows.Ensured compliance, auditability, and secure data handling in a regulated environment.
- Mercedes-Benz Mobility(prev. Financial Services)Lead Data ScientistAUTOMOBILSEKTORApril 2024 - September 2025 (1 Jahr und 5 Monate)70 Stuttgart, GermanyIntelligent Pricing Platform: Led experimentation and causal analysis for dynamic pricing and financial product optimization, supporting executive decision-making across multiple regulated markets.Recommender Systems for Global Markets (EU, China, APAC): Developed scalable custom ML pipelines on Databricks to support customer retention, pricing, and financial decisioning across EU, China, and APAC markets, contributing to €37M annual revenue impact.Product Bundling Models:Oversaw the development of ensemble and associative mining models integrating vehicle and customer data to generate personalized bundles of financial and mobility products, with a projected uplift of €4M.
- MediaMarktSaturn TechnologySenior Data ScientistE-COMMERCEMärz 2021 - Dezember 2023 (2 Jahre und 9 Monate)Munich, DeutschlandAI-Powered Customer Segmentation: Designed, built, and deployed segmentation models on Google Cloud Platform using BigQuery, Vertex AI and CloudRun to enhance audience targeting for omnichannel campaigns; improved campaign precision and led to measurable gains in ROI and personalization accuracy.Value-Based Bidding (PoC): Led an external data science consulting team to develop and test an experimental bidding optimization model for paid search; demonstrated a 35% increase in revenue through automated, value-driven ad targeting.Centralized Category Recommender System: Integrated DBT models for transformation and data standardization across regional data warehouses and led communications with Spain, Turkey and the Netherlands product owners, ensuring reproducibility and data quality for production ML pipelines, achieving a mean 20% lift in online conversion rates and standardizing deployment handover for international engineering teams.
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Ausbildung und Abschlüsse
- Master of ScienceTechnical University of Munich2025Mathematics in Data Science
- Bachelor of ScienceConstructor University (previously Jacobs University)2014Mathematics
Zertifizierungen
- Databricks Certified Generative AI Engineer AssociateDatabricks2026
- Professional Machine Learning Engineer CertificationGoogle Cloud2026