Data Scientist (AI & ML)

Tech StaQ; München; Vor Ort; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

A leading financial services organization is seeking an experienced Data Scientist to design and deploy scalable data-driven models. Candidates should have a strong background in AI, machine learning, and Python. This role involves working with stakeholders to convert data into actionable insights. You will be responsible for data preparation, model evaluation, and algorithm engineering, ensuring your contributions positively impact high-level data initiatives. The position offers a collaborative environment with professional development opportunities.

Leistungen

Professional development and certification support

Flexible work arrangements

Competitive benefits package

Qualifikationen

• 4+ years in a Data Scientist or Machine Learning Engineer role.
• Mastery of Python and core libraries (Pandas, NumPy, Scikit-learn).
• Hands-on experience with deep learning frameworks (TensorFlow or PyTorch).

Aufgaben

• Ingest and preprocess large datasets from various sources.
• Architect and deploy machine learning models to address business challenges.
• Optimize model performance using advanced frameworks.

Kenntnisse

Python

AI

Machine Learning

Data Visualization

Statistical Modeling

Ausbildung

Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, or related field

Tools

TensorFlow

PyTorch

Scikit-learn

AWS

GCP

Azure

Jobbeschreibung

Overview
A leading financial services organization is seeking an experienced Data Scientist with deep expertise in AI, machine learning, and Python development. You design, build, and deploy scalable data-driven models that solve complex business challenges and drive strategic decision-making. This role partners closely with cross-functional stakeholders to transform data into actionable insights.

Key Responsibilities

Data Collection & Preparation

• Ingest, clean, and preprocess large structured and unstructured datasets from multiple sources
• Perform exploratory data analysis (EDA) to identify trends, patterns, and data quality issues
• Develop and maintain robust ETL pipelines for efficient data transformation
• Architect, train, and deploy supervised, unsupervised, and deep learning models (classification, regression, clustering)
• Optimize model performance (accuracy, latency, scalability) using advanced frameworks (TensorFlow, PyTorch, Scikitlearn)
• Automate model retraining and monitoring workflows in production environments

Algorithm Engineering

• Design and refine algorithms for large-scale data processing and real-time inference
• Implement best practices for model interpretability, fairness, and reliability

Software Engineering & Integration

• Write clean, modular Python code following industry standards (Pandas, NumPy, SciPy)
• Integrate models into existing software platforms and cloud infrastructure (AWS, GCP, Azure)
• Maintain version control (Git) and CI/CD pipelines for reproducible deployments

Evaluation & Validation

• Define and track key performance metrics (accuracy, precision, recall, F1)
• Conduct rigorous cross-validation, A/B testing, and stress testing to ensure robustness
• Translate business requirements into technical specifications and actionable analytics solutions
• Present complex findings clearly to technical and non-technical stakeholders
• Document methodologies, code, and model decisions for transparency and audibility

Required Qualifications

• 4+ years in a Data Scientist or Machine Learning Engineer role
• Mastery of Python and core libraries (Pandas, NumPy, Scikitlearn)
• Hands-on experience with deep learning frameworks (TensorFlow or PyTorch)
• Solid understanding of statistical modeling, feature engineering, and model evaluation
• Proficiency with data visualization tools (Matplotlib, Seaborn, Plotly)
• Experience deploying models on cloud platforms (AWS, GCP, or Azure)
• Bachelors or Masters degree in Computer Science, Data Science, Mathematics, or related field

Preferred Skills

• Expertise in Natural Language Processing (NLP) or Computer Vision
• Familiarity with big data technologies (Spark, Hadoop)
• Knowledge of containerization (Docker/Kubernetes)
• Experience working in Agile/Scrum environments
• Strong written and verbal communication skills

What We Offer

• Opportunity to influence high-impact data initiatives
• Collaborative, crossdisciplinary work environment
• Professional development and certification support
• Flexible work arrangements and competitive benefits package