Senior Data Scientist

Jobgether; Deutschland; Presencial; EUR 70 000 - 110 000; Tempo integral

Resumo da oferta

Jobgether is seeking a Senior Data Scientist in Germany to lead ML, LLM, and automation initiatives. You will transform large-scale network and device telemetry into actionable insights, collaborating with product, engineering, and data teams to deliver production-ready models.

You will drive the ML lifecycle, from data preparation and feature engineering to deployment, monitoring, and optimization, influencing strategic decisions across connected environments at scale.

Qualificações

• Experience leading AI/data science projects end-to-end.
• Strong Python and SQL proficiency.
• Experience with AWS SageMaker or similar.
• Ability to translate business needs into analytical solutions.
• Production ML deployment and monitoring experience.

Responsabilidades

• Lead the development, deployment, and ongoing improvement of ML, LLM, and automation projects.
• Process, analyze, and transform large-scale telemetry datasets to support modeling and decision-making.
• Design feature engineering strategies to improve model performance and interpretability.
• Build analytical pipelines using Python/SQL and deliver reproducible results.
• Develop and evaluate ML models for anomaly detection, forecasting, and optimization.
• Collaborate with product and engineering to productionise models and measure value.

Conhecimentos

Lead AI projects

Python

SQL

ML/LLMs

MLOps

Ferramentas

Pandas

NumPy

Scikit-learn

AWS SageMaker

Amazon S3

Descrição da oferta de emprego

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in Germany. Join an innovative technology team developing AI-powered solutions for connected homes, businesses, and enterprise environments at global scale. As a Senior Data Scientist, you will lead machine learning, large language model (LLM), and automation initiatives that transform large volumes of network and device telemetry into actionable insights. You will combine advanced analytical techniques with practical engineering to solve complex problems involving anomaly detection, forecasting, and optimization. Working closely with product, engineering, and data teams, you will help translate business needs into reliable models and production-ready solutions. You will contribute throughout the machine learning lifecycle, from data preparation and feature engineering to deployment and performance monitoring. This role offers the opportunity to shape intelligent connected-space experiences in a fast-moving, collaborative, and innovation-driven environment.

Accountabilities

• Lead the development, implementation, maintenance, and continuous improvement of machine learning, LLM, and automation projects.
• Process, clean, transform, and analyze large-scale network and device telemetry datasets to create reliable inputs for modeling and decision-making.
• Design and implement feature engineering strategies that improve model accuracy, interpretability, robustness, and overall performance.
• Use Python and SQL to explore complex datasets, build analytical pipelines, and deliver reproducible, high-quality results.
• Develop and evaluate machine learning models for use cases such as anomaly detection, forecasting, and system optimization.
• Translate product and business requirements into clearly defined analytical problems, project scopes, and model development plans.
• Collaborate with engineering and product teams to integrate machine learning models into production systems and ensure they deliver measurable value.
• Balance experimentation with execution by prioritizing high-impact work and delivering reliable insights and models within demanding timelines.
• Contribute to MLOps workflows, including model deployment, validation, monitoring, and ongoing performance improvements.
• Identify opportunities to apply AI and automation techniques to improve operational efficiency, analytical capabilities, and connected-device experiences.
• Communicate findings, technical approaches, and model outcomes clearly to cross-functional stakeholders, supporting informed product and business decisions.

Requirements

• Demonstrated experience leading, developing, and owning AI or data science projects from initial scoping through implementation and ongoing improvement.
• Strong practical knowledge of machine learning techniques, LLMs, and their application to real-world problems.
• Advanced Python programming skills, including experience with data science and machine learning libraries such as Pandas, NumPy, and Scikit-learn.
• Solid SQL skills, with the ability to query, aggregate, and join complex datasets efficiently.
• Proven experience transforming messy, high-volume data into structured, high-quality datasets suitable for analytical and predictive modeling.
• Strong understanding of feature extraction, selection, and transformation techniques, with an emphasis on improving model performance and interpretability.
• A solid foundation in statistics, probability, and applied machine learning, including model evaluation and validation.
• Experience translating business or product requirements into practical analytical solutions and delivering high-quality work under tight deadlines.
• Familiarity with deploying and monitoring machine learning solutions in production, including MLOps practices and workflows.
• Experience with AWS cloud services, particularly SageMaker and Amazon S3, or comparable cloud-based machine learning infrastructure.
• Strong communication, collaboration, and problem-solving skills, with the ability to work effectively across engineering, product, and data teams.
• A proactive, adaptable approach to technical challenges, with the ability to balance analytical rigor, experimentation, and efficient delivery.

Benefits

• The opportunity to work on AI and machine learning solutions supporting connected environments at substantial global scale.
• Exposure to advanced technologies spanning network telemetry, smart spaces, machine learning, LLMs, and cloud-based platforms.
• The opportunity to lead and influence AI projects from development through production deployment and ongoing optimization.
• A collaborative, innovation-focused environment that encourages curiosity, creative problem-solving, and high-quality technical work.
• The opportunity to partner with major internet service providers and contribute to technology used across millions of locations and billions of managed devices.
• An inclusive, equal-opportunity workplace committed to fair employment practices and nondiscrimination.
• Salary, equity, healthcare, paid leave, and specific remote-work arrangements are not detailed in the provided job description and should be confirmed during the recruitment process.