Carsten Trumm

As an IT solution provider for digital customer management, we develop tailor-made solutions for and with companies.

We support you in digitizing your customer management from requirements definition through customization & implementation to maintenance.

With the right balance of consulting and implementation expertise, we are at your side in every phase of digital transformation.

Business Concepts

Marketing & CRM Concepts

Marketing

AutomationPermission Management

Governance

IT Services & AI

Architecture & Solution Design

Software Implementation

Software Configuration

System Integration

Data Services / Data Loading

Data Quality Management

Applied AI / AI

Project Support

IT Project Management

Data Product Management

Change Management

Business Process Outsourcing

Training and Support

Data & Analytics

Reporting & Dashboards

Business Insights & Ad hoc Analytics

Data Quality Management

Transforming raw data into features used by ML training processes, creating new data based on exploratory analysis, extract information and monitoring quality and content for better AI models.

· Transitioning the team from the consumer sector to a centralized Data & Analytics organization in Finance

· Implementation of the One Data Strategy (aggregation of functions from various teams in the Consumer, Finance, and Customer Operations areas)

· Introduction of the Vertex AI Feature Store with a focus on real-time feature serving for Smart Routing (live assignment of customers to inbound agent teams)

· Introduction of standardized monitoring for measuring ML success criteria (Accuracy, Precision, Recall, F1-Score, ROC-AUC)

· Completion of data integration strategy and historization of feature marts up to 25 months, considering GDPR and TKG regulations

· Pre-qualification in the development of features using AutoML

· Iterative improvement of features through data visualization and fast-track model integration, as well as cross-team organized feedback loops

Managing Data for Big Data Use Cases in the Consumer environment, including data and feature engineering for all AI use cases according to CI/CD standards.

· Functional and disciplinary leadership of two teams at different locations with up to 9 employees in two tiers

· Requirements-based development of data products for machine learning use cases, particularly data cleansing, data quality monitoring, exploratory data analysis, and feature engineering in a multi-system and product-based market

· Continuous documentation of data structures and software development, as well as introduction and use of release management methods via GitHub

· Cross-departmental interface for data-related topics with Data Engineering and other Data Science departments within the company, active coordination on interdisciplinary and domain-specific issues in Sales, Marketing, Customer Experience, and Network Technology

· Functional responsibility for Footprint Management: data representation of Vodafone GmbH's communication network (all fixed lines), bandwidth availability information for customer inquiries, calculation of the company KPI "Homes Passed", continuous updating of the Germany-wide address database, and supplementation with socio-demographic information to support, for example, the company's marketing activities