Data Scientist Machine Learning & Predictive Analytics

Project overview

For our client, we are looking for a Data Scientist Machine Learning & Predictive Analytics to support the central research and development department in developing data-driven solutions for product development and performance optimization.

Responsibilities

• Development, validation, and optimization of machine learning models for predicting product and catalyst performance
• Creation of forecast models for emissions and performance indicators based on scientific, experimental, and technical data
• Conducting exploratory data analyses (EDA), data preparation, feature engineering, and correlation analyses
• Identification of patterns, influencing factors, and optimization potential in complex research, laboratory, and process data
• Development of robust predictive analytics approaches to support data-based decisions in research and product development
• Collaboration with Data Engineers, researchers, engineers, and business stakeholders to provide reliable analyses
• Documentation of methods, assumptions, validation results, and recommendations for action
• Presentation of results to technical and non-technical stakeholders
• Support in transferring prototypes and analyses into scalable, reusable modeling solutions

Requirements

Framework Data

Sounds exciting? Then I look forward to your application!

• Completed Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Physics, Chemistry, Materials Science, or a comparable field
• Approx. 2-4 years of professional experience in Data Science, Machine Learning, statistical modeling, or Predictive Analytics
• Sound programming skills in Python and experience with Pandas, NumPy, Scikit-learn, and Matplotlib
• Experience in data analysis, data cleaning, data preparation, and feature engineering
• Knowledge in the development and evaluation of forecast models based on complex technical or scientific data
• Understanding of model validation, data quality, reproducibility, and model interpretation
• Experience with structured industrial, research, laboratory, or engineering data
• Ability to comprehensibly prepare and visualize analytical results
• Ideally, experience with Gradient Boosting, regression and classification models, Bayesian approaches, or Physics-Informed Machine Learning
• Advantageous: Knowledge of SQL, Azure Machine Learning, Databricks, or comparable cloud and data science platforms
• Independent, analytical, and structured way of working
• Strong communication and stakeholder management skills
• Fluent English; German language skills are an advantage
• Location: Hanau, Germany
• Work Model: Hybrid
• On-site component: 3 days per week
• Utilization: Full-time (40 hours per week)

Project details

• Start: ab sofort
• Remote: hybrid
• Location: Hanau, Deutschland, DE
• Languages: German