Dataiku Experts in Germany

• Defined the vision, strategy, and roadmap of AI-powered analytics products, ensuring they met the business needs of Sales, Marketing, Finance, and executive teams across Europe.
• Collected business requirements, prioritized AI product features, and led Agile development of forecasting and analytics solutions. Defined product specifications, user stories, and acceptance criteria to ensure successful delivery.
• Collaborated with business stakeholders, Product Owners, data scientists, ML engineers and software engineers to transform AI models into scalable business products and integrate AI insights into operational workflows.
• Designed and implemented Generative AI solutions leveraging Large Language Models (LLMs) to automate reporting and enable natural-language querying of enterprise data, reducing manual effort by approximately 30%.
• Defined product goals and success metrics, tracked product performance and user adoption, and continuously improved the product based on user feedback and business results.
• Established data governance, master data quality and reporting standards across SQL, BigQuery and Power BI environments to ensure reliable, secure and scalable analytics.

• Project environment: Python, Java, Azure AI Studio & OpenAI Studio, embedding models, LLM as a judge
• Project language: German
• Project role(s): Project manager
• Project management for improving the performance of a chatbot
• Research and evaluation of approaches to improve and measure response accuracy and improve the chatbot's understanding of context
• Coordination of architecture decisions with the technical team and architects
• Coordination and transfer of research results into development tasks

• Providing consulting services for Turkish clients planning to move to Germany (work, study, and family reunification visas).
• Preparing personalized immigration strategies, document checklists, and digital handbooks.
• Supporting clients with CV and motivation letter preparation in line with German standards.
• Managing email marketing automation, newsletter workflows, and audience segmentation to increase client engagement.
• Designing and maintaining CRM integrations between Wix, HubSpot, and Zapier for automated client onboarding and follow-up.
• Handling sales operations, including deal and support pipelines, workflow automation, and client relationship tracking within HubSpot.
• Managing invoicing and budget tracking via Lexoffice, ensuring accurate reporting and financial transparency.
• Developing and optimizing digital funnels, landing pages, and online courses for lead generation and conversion.
• Overseeing content creation and performance marketing campaigns on Instagram, YouTube, and Google Ads.

• Developed a comprehensive business concept for a medical fall detection device based on a patented process registered in Germany
• Identified and collected use cases for medical device deployment in residential buildings and healthcare provider facilities
• Expanded the product scope to industry standards such as HL7/FHIR and designed a product based on modern communication protocols for IIoT
• Supported offshoring activities, defined SLA and scope-of-work documents for development teams after selecting various vendors
• Identified and selected hardware components (Terrabee, E-Con Systems) for LIDAR/TDOA functions
• Defined integrated AI features and LLM models for patient fall detection as well as AI-based audio triggers
• Oversaw the implementation of algorithms for object detection, fall detection, and false alarm identification

• Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
• Performance Optimization of Data Ingestion of ETL Pipeline
• Development of Data Validation using Great Expectations
• Leading of the data migration for two sources exchanges
• Data Modeling in AWS Redshift

MLOps

• Model inference implementation by mlflow and AWS SageMaker
• Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
• Implementatino of Model Registry and artifactory using mlflow
• Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
• Feature importance using mlflow

Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy

• Built a CRNN model with VGG16 and BiLSTM backbone for text-based CAPTCHA recognition
• Achieved 9.37% character error rate and 68.36% sequence accuracy on validation data
• Expanded data augmentation pipeline with distortions, noise injection, and clutter to improve robustness
• Conducted detailed error analysis on confusable characters (O, Q, D) and proposed error-specific augmentation
• Tech Stack: Python, TensorFlow/Keras, OpenCV, NumPy, Matplotlib

• Built scalable end-to-end machine learning pipelines for a major telco company, covering feature engineering, model development, deployment, and a Streamlit visualization app.
• Initiated and embedded data science within the Customer Experience team, collaborating daily with stakeholders to deliver end-to-end solutions; under my ongoing support, customer satisfaction score, NPS, remained stable at a record >30pt.
• Advised a client on GenAI tools, AI development strategies, and Responsible AI practices, shaping internal adoption and governance approaches.