Objective of Job

1.Technical responsibility for the analytical value chain in the Sales Planning & Logistics department – transforming business challenges in the area of Sales Planning, Ordering, and Logistics into AI-based use-cases by developing innovative algorithms, implementing scalable solutions, and enabling business users and colleagues to apply these solutions.

2.Translate business issues into suitable data science concepts by identifying and clustering potential uses cases in Sales Planning, Ordering, and Logistics and applying, e.g., regression, classification, clustering, anomaly detection, recommendation systems, time series forecasting, natural language processing, etc.

3.Lead and drive technical operationalization and further development of the ‘DDx’ project to enable Data-Driven Forecasting (DDF) and Data-Driven Incentives (DDI) together with the business and data science teams from the involved business partner departments.

4.Extract, process, and validate sales, sales planning, ordering, and logistics data from data lakes and data bases by applying data science, data analytics, and data mining methods and tools (e.g., SQL, Python, R, etc.).

5.Assist in market, sales planning/forecasting, ordering, and logistics trend, as well as ad-hoc analyses.

6.Support accurate and timely preparation of reports and management presentations including state-of-the-art, simple, and concise data visualization.

7.Act as main point of contact and interface between Data Science, IT, and Sales Planning & Logistics business.

8.Collaborate cross-functionally with business partner data scientists and data teams to ensure BMBS-wide value creation and synergies out of the available data at BMBS.

Task Description

1. Technical Responsibility for Analytical Value Chain
-Transform business challenges in the area of Sales Planning, Ordering, and Logistics into AI-based use-cases by developing innovative algorithms, implementing scalable solutions, and enabling business users and colleagues to apply these solutions.
-Translate business issues into suitable data science concepts by identifying and clustering potential uses cases in Sales Planning, Ordering, and Logistics and applying, e.g., regression, classification, clustering, anomaly detection, recommendation systems, time series forecasting, natural language processing, etc.
-Lead and drive technical operationalization and further development of the ‘DDx’ project to enable Data-Driven Forecasting (DDF) and Data-Driven Incentives (DDI) together with the business and data science teams from the involved business partner departments.

2.  Data Extraction & Processing
-Extract, process, and validate sales, sales planning, ordering, and logistics data from data lakes and data bases by applying data science, data analytics, and data mining methods and tools (e.g., SQL, Python, R, etc.).
-Assist in market, sales planning/forecasting, ordering, and logistics trend, as well as ad-hoc analyses.
-Cleanse and validate data to ensure accuracy and consistency.

3. Reporting & Data Visualization
-Support accurate and timely preparation of reports and management presentations including state-of-the-art, simple, and concise data visualization.
-Lead and/or support automation and advancement of existing as well as creation of new, valuable analyses, reports, and dashboards for sales KPIs, sales planning data, ordering data, or logistics data.

4. Cross-Functional Data Collaboration
-Act as main point of contact and interface between Data Science, IT, and Sales Planning & Logistics business.
-Collaborate cross-functionally with business partner data scientists and data teams to ensure BMBS-wide value creation and synergies out of the available data at BMBS.

5. Process & Data Governance
-Document data extraction, processing and reporting processes.
-Work with Data Science/IT teams to improve data structures and reporting efficiency.
-Ensure compliance with data security and governance policies.

Qualification

- Degree in Data Science, Computer Science, Business Administration with a focus on Business Informatics, Financial Mathematics, or a comparable qualification
- Professional experience in applying data science, data analytics, and data mining, e.g., in modeling multidimensional structures and using data lakehouse systems (Azure, Databricks)
- Solid understanding of data science, data analytics and big data concepts, methods, and tools, including programming languages like Python and R
- Understanding of modern machine learning techniques and their mathematical foundations, as well as their business implications, e.g., Generalized Linear Models, Decision Trees, Ensemble Methods, Neural Networks, Generative Models, and Large Language Models
- Experience in Data Engineering & DevOps is a plus
- Strong IT affinity and willingness to learn, particularly advanced knowledge in using BI tools (e.g., Power BI), and expertise in data analytics
- English level-CET 6 and above
- Reliable, highly quality-conscious, solution-oriented, and independent working style with strong goal and results orientation
- Strong analytical thinking skills and highest level of comprehension in an increasingly complex business environment
- Excellent communication and teamwork skills