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(Junior) Data Scientist (f/m/d) - Job Opportunity at smartclip Europe GmbH

Berlin, Germany
Full-time
Entry-level
Posted: June 7, 2025
Hybrid
€45,000 - €65,000 annually for junior level in Berlin/Hamburg market, with strong growth potential to €80,000+ within 2-3 years given the specialized nature of ad-tech data science

Benefits

Cutting-edge hardware provisioning including Mac/Linux systems providing significant productivity advantages over standard corporate equipment
Comprehensive professional development investment through paid Coursera and Udacity access plus conference and hackathon attendance representing substantial annual value
Innovative 4-day workweek 'Smart Fridays' policy offering superior work-life balance compared to traditional 5-day schedules
Complete flexibility in work arrangements with remote options and flexible hours demonstrating high trust and autonomy
Mobility benefits including JobRad bicycle leasing and Urban Sports Club membership plus entertainment perks with RTL+ subscription
Transportation cost support through Deutschlandticket subsidy reducing commuting expenses significantly

Key Responsibilities

Lead exploration and analysis of terabyte-scale real-world datasets to drive strategic business insights and competitive advantages in the digital advertising space
Architect and develop innovative data products and machine learning models that directly impact revenue generation and operational efficiency
Conduct advanced experimental design and statistical analysis to solve novel problems without established solutions, contributing to industry knowledge
Drive technical decision-making by selecting optimal tools and methodologies based on problem requirements rather than technology trends
Collaborate with domain experts to translate complex business challenges into scalable data science solutions with measurable impact
Build and maintain robust ML pipelines and data infrastructure that supports enterprise-level decision making

Requirements

Education

Bachelor's degree or equivalent in quantitative field

Experience

Entry to junior level experience in data science

Required Skills

Python – comfy with pandas, scikit-learn & friends Data Science basics – from feature engineering to model validation SQL – joins, aggregations, subqueries Docker & Linux – smooth setup and deployment AI/ML – real models, not just slide decks Git – because version control is second nature
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Sauge AI Market Intelligence

Industry Trends

The digital advertising technology sector is experiencing rapid consolidation with increased demand for data scientists who can work with real-time bidding systems and programmatic advertising platforms. Companies are moving away from basic analytics toward sophisticated ML models that can process billions of ad requests daily and optimize campaign performance in milliseconds. European data privacy regulations including GDPR have created significant demand for data scientists who understand privacy-preserving analytics and can build compliant ML systems. The cookieless future is driving innovation in first-party data utilization and contextual advertising technologies. The industry is shifting from dashboard-heavy reporting to predictive and prescriptive analytics, with emphasis on causal inference and experimentation. Companies are investing heavily in data scientists who can move beyond correlation to establish causation and drive actionable business insights.

Role Significance

Likely working within a small, specialized data science team of 3-8 professionals, with close collaboration across engineering and product teams in a flat organizational structure typical of European tech companies
Junior to mid-level individual contributor role with significant autonomy and technical decision-making authority. The position offers unusual independence for a junior role, suggesting the company values innovation and self-direction over traditional hierarchical management.

Key Projects

Real-time bid optimization algorithms processing millions of advertising requests per second Attribution modeling and incrementality testing for multi-channel advertising campaigns Audience segmentation and lookalike modeling using privacy-compliant methodologies Campaign performance prediction models and automated optimization systems Cross-platform measurement and unified customer journey analytics

Success Factors

Strong foundation in statistical thinking and experimental design to move beyond correlation and establish causal relationships in complex advertising ecosystems Pragmatic approach to tool selection and problem-solving, focusing on business impact rather than following technology trends or implementing solutions for their own sake Ability to work independently with minimal supervision while collaborating effectively in a team environment, balancing autonomy with knowledge sharing Deep curiosity and persistence in tackling novel problems without established solutions, essential in the rapidly evolving ad-tech landscape Strong communication skills to translate complex technical findings into actionable business insights for non-technical stakeholders

Market Demand

High demand driven by digital advertising growth, privacy regulation compliance needs, and the technical complexity of real-time bidding systems requiring sophisticated data science capabilities

Important Skills

Critical Skills

Python proficiency with pandas and scikit-learn is absolutely essential as these form the foundation for daily data manipulation, analysis, and model development in the fast-paced ad-tech environment where rapid prototyping and iteration are crucial for competitive advantage. SQL expertise for complex queries and data aggregation is critical given the massive scale of advertising data processing, where efficient database queries can mean the difference between real-time insights and delayed decision-making that costs revenue. Machine learning fundamentals including feature engineering and model validation are vital for building robust predictive systems that must perform reliably in production environments processing millions of advertising decisions daily. Git version control mastery is essential for collaborative development in a technical team environment where code quality and deployment reliability directly impact business operations and revenue generation.

Beneficial Skills

Apache Spark knowledge becomes increasingly valuable for processing the terabyte-scale datasets mentioned in the role, enabling career progression toward senior positions handling enterprise-level data infrastructure and distributed computing challenges. Container orchestration with Kubernetes and workflow management tools like Airflow or Prefect represent the future of scalable ML operations, positioning candidates for technical leadership roles in data engineering and MLOps. Large Language Model tooling and frameworks like PyTorch are emerging as critical differentiators in ad-tech applications for content analysis, creative optimization, and automated campaign management. Shell scripting capabilities enhance productivity and enable automation of routine tasks, freeing up time for higher-value analytical work and demonstrating technical maturity appreciated in senior data science roles.

Unique Aspects

Opportunity to work with terabyte-scale real-world advertising data rather than academic datasets, providing exposure to genuine big data challenges and industry-relevant problems
Strong emphasis on practical problem-solving over trendy technologies, creating an environment focused on business impact and technical substance rather than resume-driven technology choices
Unusual level of autonomy for a junior position, with freedom to choose methodologies and tools while working on undefined problems that contribute to industry knowledge
Access to open-source contributions and technical visibility through the company's GitHub presence, enabling professional development and industry recognition
4-day workweek policy providing competitive advantage in attracting top talent while maintaining productivity through focused work periods

Career Growth

Rapid progression potential with 18-24 months to senior level given the specialized nature of ad-tech data science and high industry demand for experienced practitioners

Potential Next Roles

Senior Data Scientist specializing in ad-tech and programmatic advertising within 2-3 years Lead Data Scientist or Principal Data Scientist roles focusing on ML infrastructure and model architecture Product Data Science roles bridging technical analysis with product strategy and user experience optimization Data Science Manager positions leading teams in high-growth European tech companies

Company Overview

smartclip Europe GmbH

smartclip Europe GmbH is a significant player in the European digital advertising technology ecosystem, operating across multiple markets including Germany and other European countries. The company focuses on video advertising solutions and programmatic advertising platforms, positioning itself as a technology-driven alternative to traditional advertising networks.

Established European ad-tech company with strong regional presence and technical reputation, competing effectively against both global ad-tech giants and local competitors through specialized video advertising solutions and programmatic capabilities
Strong presence in German-speaking markets with expansion across Europe, offering opportunities to work on international campaigns and cross-cultural advertising challenges while remaining within the European regulatory and business environment
Progressive European tech culture emphasizing work-life balance, technical excellence, and employee autonomy. The 4-day workweek and flexible arrangements suggest a company that prioritizes employee satisfaction and productivity over traditional corporate structures.
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