Job
- Level
- Experienced
- Job Field
- Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Hörsel
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you develop ML models for predicting churn and financial KPIs, operationalize them on Microsoft Fabric, and support business users with interactive data queries.
Job Technologies
Your role in the team
- ML model development for Advanced & Predictive Analytics: Development of predictive models for Churn Prediction, Forecasting, Demand Planning, as well as financial metrics (e.g., LO, LOA, Gross Margin, Net Profit).
- Predictive 'Ask your Data' Use Cases: Enabling interactive, AI-powered data queries for business users.
- Delivery of AI use cases: forecasting & prediction, anomaly detection, data mining & pattern recognition; providing predictive insights for operational and financial control.
- Operationalization of ML models on Microsoft Fabric: Deployment and maintenance of ML models on the MS Fabric platform; utilization of Fabric's ML capabilities for production workloads.
- AI for data-driven value creation: alignment with CHG's AI strategy; close collaboration with Senior AI Engineer(s) on AI use cases.
- Feature Engineering & Data Preparation: Cleaning, transforming, and preparing data for ML models.
- Model validation & backtesting: Ensuring prediction accuracy through rigorous testing methods.
- Domain-specific AI use cases: e.g., residual value prediction, eFMV estimation, remarketing price optimization, credit risk assessment.
- Knowledge Transfer: Empowering Citizen Data Scientists and Business Analysts to utilize ML outputs.
- Collaboration with Data Engineers: Ensuring that data pipelines meet the requirements of the ML models.
This text has been machine translated. Show original
Our expectations of you
Education
- Experience: 3-5 years of professional experience in Data Science / Machine Learning; completed degree in Computer Science, Business Informatics, Mathematics, or a related field.
Qualifications
- Technical foundational competence: data modeling (conceptual, logical, physical), Power BI, MS Fabric.
- Programming: Python, PySpark, SQL.
- ML frameworks: TensorFlow, PyTorch, Scikit-learn or comparable technologies.
- Statistical modeling: regression, classification, time series forecasting, clustering.
- Cloud ML platforms: MS Fabric, Azure ML, or comparable cloud-native ML services.
- Data Processing: Spark, Distributed Computing for Large-Scale Analytics.
- Soft skills: Strong analytical thinking, ability to translate business requirements into ML solutions, high sense of responsibility.
- Domain knowledge: Basic understanding of Data Mesh, Data Products, Data Governance, and Data Lakehouse architecture.
- Language skills: Very good spoken and written English and German.
This text has been machine translated. Show original
What we offer
- Mobile and flexible working, 30 days of vacation, and the opportunity for 20 days of Workation (within the EU).
- Individual onboarding as well as personal and professional development opportunities supported by our People Development Team.
- Corporate health management with fitness and sports offerings (EGYM Wellpass, sports events, health weeks).
- Employer subsidy for asset-building benefits.
- Latest generation mobile devices also for private use.
- Additional benefits for you include asset-building payments, bicycle leasing, discounted leasing of new IT devices for private use, and corporate benefits.
This text has been machine translated. Show original
Benefits
More net
Work-Life-Integration
Health, Fitness & Fun
Food & Drink
Topics that you deal with on the job
Job Locations
This is your employer
CHG-MERIDIAN
At CHG-MERIDIAN, we're leaders in the IT, industrial, and medical technology fields. We're an independent company that prides itself on experience and innovation.
Description
- Company Size
- 50-249 Employees
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Industry, Production, Internet, IT, Telecommunication
Senior Data Scientist
- Location
- Hörsel
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
