data scientist in media intelligence

Enfint; Deutschland; Hybrid; EUR 78.000 - 123.000; Vollzeit

Benefits dieser Stelle

Private health insurance

Certification reimbursement

Corporate events and amenities

Zusammenfassung

Andersen ищет ведущего дата-сайентиста для развертывания крупных проектов в области анализа данных и AI‑решений. Вы будете принимать решения по методологиям, проектировать решения и обеспечивать качество кода на Python и Databricks.

Кандидат должен иметь опыт MLOps, знание SQL/PySpark и владение облачными платформами AWS или GCP. Роль допускает гибридный формат работы и развитие в динамичном кросс-функциональном окружении.

Qualifikationen

• 3+ года практического опыта в Data Science и владение несколькими спринтами.
• Степень бакалавра в статистике/науке о данных/CS/математику или эквивалент.
• Продвинутый Python: продакшн-код, хорошо документированный.

Aufgaben

• Руководство внедрением крупных проектов Data Science от идеи до продакшна.
• Документация методологий, выбор моделей и оценок.
• Ведение проектной документации и координация команд.

Kenntnisse

Python

SQL

Data modeling

Machine Learning

English proficiency

Ausbildung

Bachelor's degree in Statistics/Data Science/CS/Math

Tools

Databricks

Airflow

Delta Lake

AWS/GCP

Jobbeschreibung

Описание: Andersen is a global technology provider delivering data analytics and AI-powered solutions that help organizations understand customer behavior, optimize marketing performance, and make informed business decisions. Its media intelligence project analyzes consumer engagement across TV, digital, and connected devices using real-time, consented data to provide audience insights and content analytics for media and advertising.

Задачи

• Own end-to-end delivery of significant data science projects from problem scoping and approach design through production deployment;
• Make independent decisions on methodology, model selection, and evaluation, and document them in technical solution documents;
• Lead solution design for individual initiatives;
• Break down complex epics into well-scoped user stories with clear acceptance criteria;
• Apply DataOps and MLOps best practices, including experiment tracking, pipeline orchestration, model monitoring, and reproducibility;
• Build production-quality Python and PySpark code on Databricks;
• Implement advanced ML and AI-powered workflows, including entity resolution, probabilistic record linkage, embedding-based matching, semantic similarity, and LLM-augmented pipelines;
• Develop and maintain reusable tools, libraries, and documentation that improve team efficiency and technical standards;
• Conduct code reviews with constructive and specific feedback;
• Mentor junior data scientists on technical execution, code quality, and career development;
• Lead internal talks or workshops on ML topics;
• Collaborate with product, engineering, and operations teams;
• Translate business requirements into technical specifications;
• Partner with data engineering on scalable pipeline design;
• Participate in cross-functional design reviews and working groups.

Требования

• 3+ Years of hands‑on Data Science experience, including ownership of complex multi-sprint projects;
• Bachelor’s degree in Statistics, Data Science, Computer Science, Mathematics, or another quantitative field;
• Advanced Python proficiency, including production-quality, well-tested, and well-documented code;
• Strong SQL and PySpark experience with billion-row datasets;
• Hands‑on Databricks experience, including Workflows, Delta Lake, and job orchestration;
• Working knowledge of AWS or Google Cloud Platform;
• Strong foundation in Machine Learning, including regression, classification, clustering, model evaluation, and experimental design;
• Experience with MLOps practices, including experiment tracking, Airflow‑based pipeline orchestration, and reproducible model deployment;
• Familiarity with RAG, LLM-based applications, vector databases, and semantic search;
• Strong written and verbal communication skills;
• English at Intermediate+ level or above;
• Nice to have: Master’s degree, knowledge graph construction, entity resolution, semantic data modeling, probabilistic record linkage, identity graph approaches, embedding-based entity matching at scale, causal inference, A/B testing, synthetic control, uplift modeling, deduplication, data enrichment, web-to-TV linkage, media or ad tech experience, TV viewership, digital audience modeling, cross-platform measurement, privacy-constrained identity resolution, familiarity with Nielsen, Comscore, LiveRamp, and The Trade Desk.

Условия

• The role can be performed fully remotely, from the office, or in a hybrid format;
• Opportunity to change projects and develop expertise in an interesting business domain;
• Professional, financial, and career growth opportunities;
• Mentoring and onboarding systems for each new employee;
• Opportunity to earn up to an additional 1,000 EUR per month depending on expertise, included in the annual bonus;
• Access to the corporate training portal;
• Certification compensation, including AWS and PMP;
• Private health insurance and sports compensation depending on the type of employment;
• Corporate events and amenities, including parties, pizza days, PlayStation, fruits, coffee, snacks, and movies.