Senior Data Scientist

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Job Responsibilities:

1. Develops and refines machine learning models to solve specific business problems (Model Training)
2. Conducts feature engineering to enhance model performance and represent data optimally
3. Performs hyperparameter tuning to optimize model performance
4. Designs and implements ML pipelines that sequence different steps for optimal results (e.g., model training, evaluation, data transformation)
5. Selects appropriate algorithms based on problem requirements, data characteristics, and performance criteria
6. Analyzes data to uncover trends, patterns, and insights
7. Considers and accounts for data drift over time to ensure models remain effective in production
8. Conducts prompt engineering to improve performance of models requiring natural language inputs
9. Ensures quality through model evaluation and rigorous testing of results
10. Estimates costs for ML-related tasks, including project offers and change requests
11. Collaborates with business stakeholders to deeply understand the business case behind the ML model and its expected outcomes

Requirements:

1. Strong knowledge of machine learning algorithms, hyperparameter tuning, and model evaluation
2. Experience with prompt engineering and natural language processing (NLP) tasks
3. Proficiency in Python
4. Familiarity with ML libraries such as TensorFlow, Scikit-learn, and PyTorch
5. Knowledge of data analysis techniques, feature engineering, and data preparation
6. Understanding of ML pipelines and workflow automation
7. Ability to detect and address data drift in production environments
8. Strong problem-solving and analytical thinking skills
9. Experience working with stakeholders to understand and refine business cases
10. Familiarity with cost estimation and budget management for ML projects
11. Excellent communication skills to convey technical insights in business terms
12. Continuous learning mindset, staying updated with the latest in AI/ML technologies

Primary Skills:

1. Core Libraries: Python 3.11+, pandas, NumPy, scikit-learn
2. Deep Learning: TensorFlow, Keras, PyTorch
3. Development & Deployment: Git, Docker
4. Data Visualization & Application: Streamlit, Matplotlib

Computer Software & Networking 101-1,000 employees

As an internationally active IT specialist, Arvato Systems supports renowned companies in their digital transformation. Around 3,400 employees at over 25 locations worldwide stand for a high level of technical understanding, industry expertise and a clear focus on customer needs. As a team, we develop innovative IT solutions, bring our customers into the cloud, integrate digital processes and take over the operation and support of IT systems. Through our strong strategic partner network with international top players such as AWS, Microsoft, Google or SAP, we continuously strengthen our technological know-how and rely on state-of-the-art technology with and for our customer(s).