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Logistics Data Analyst (m/f/d) - Job Opportunity at Flink

Berlin, Germany
Full-time
Mid-level
Posted: July 10, 2025
On-site
€55,000 - €70,000 per year based on Berlin market rates for mid-level data analysts in high-growth tech companies, with potential for performance bonuses and equity participation given Flink's rapid expansion and strong investor backing

Benefits

€1,000 annual learning and development budget with individual coaching options, providing substantial investment in professional growth that exceeds typical market offerings
26 vacation days with annual increases up to 30 days maximum, demonstrating progressive benefits that reward tenure and support work-life balance
€35 monthly mobility budget for Deutschland Ticket subsidy, offering practical transportation support that reduces commuting costs
Urban Sports Club membership discount, providing access to premium fitness facilities and wellness programs
Attractive company pension options, ensuring long-term financial security with employer contribution to retirement planning
Unlimited access to MyAcademy e-learning platform including German language courses, supporting continuous skill development and cultural integration
Corporate Benefits and Future Bens online discount programs, extending cost savings beyond workplace perks
Personal Flink order discounts with early access to new products, offering insider benefits and product testing opportunities
Modern dog-friendly office environment in central Berlin with diverse dining options, creating an inclusive and convenient workplace atmosphere

Key Responsibilities

Lead conceptualization and coordination of operational efficiency initiatives through strategic product and process improvements, directly impacting company-wide performance metrics and competitive positioning
Transform deep operational insights into actionable improvement strategies for data science teams, serving as the critical bridge between operational reality and analytical solutions
Oversee comprehensive testing and optimization of logistics technology stack to drive measurable operational impacts, ensuring technological investments deliver quantifiable business value
Empower C-level decision makers through strategic reporting, executive dashboards, and critical ad-hoc analysis that directly influences corporate strategy and resource allocation
Develop sophisticated business outcome models and long-term projections that form the foundation for strategic business planning and investor communications
Collaborate across multiple high-impact teams including HQ product, engineering, data science, and local operations, facilitating cross-functional alignment and strategic execution

Requirements

Education

Bachelor or Masters degree in Mathematics, Statistics, IT, Finance or similar area

Experience

At least 2 years of work experience in a quantitative field - e.g. consulting, operations (experience in an instant-delivery environment is a plus)

Required Skills

Solid knowledge of statistical testing methodologies Very good working knowledge of SQL Previous experience working with R, or Python and common data libraries Experience with Python for unstructured data, machine learning techniques are advantageous Good knowledge of MS Office, specially Excel (familiarity of their Google Workspace equivalents is a plus)
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Sauge AI Market Intelligence

Industry Trends

Quick commerce and instant delivery markets are experiencing explosive growth across Europe, with the sector expanding at over 40% annually as consumer expectations shift toward immediate gratification and convenience. Companies like Flink are pioneering this transformation, requiring sophisticated data analytics to optimize delivery routes, inventory management, and operational efficiency in real-time logistics networks. Sustainability initiatives are becoming critical differentiators in the logistics sector, with electric vehicle adoption and recyclable packaging driving operational complexity. Data analysts in this space must now factor environmental impact metrics into their optimization models, creating new analytical challenges that combine traditional logistics efficiency with carbon footprint reduction. The integration of machine learning and AI into logistics operations is accelerating, with companies investing heavily in predictive analytics for demand forecasting, route optimization, and inventory management. This trend is creating increased demand for analysts who can bridge the gap between traditional logistics operations and advanced data science applications.

Role Significance

Typically part of a 5-8 person data and analytics team, with close collaboration across product, engineering, and operations teams totaling 20-30 cross-functional partners
Mid-level individual contributor role with significant strategic influence, positioned as a key bridge between operational teams and senior leadership, with direct impact on company-wide efficiency initiatives and executive decision-making processes

Key Projects

Implementation of predictive demand forecasting models to optimize inventory allocation across multiple cities and reduce stockouts Development of real-time delivery route optimization algorithms to improve delivery times and reduce operational costs Creation of comprehensive operational dashboards for C-level executives to monitor key performance indicators and strategic metrics Analysis and optimization of warehouse operations and fulfillment processes to support rapid geographic expansion

Success Factors

Strong ability to translate complex operational challenges into clear analytical frameworks that can drive actionable business improvements and strategic decisions Excellence in stakeholder management and communication, particularly with senior leadership and cross-functional teams, requiring the ability to present technical findings in business-relevant terms Deep understanding of logistics and supply chain operations combined with advanced analytical skills to identify optimization opportunities that others might miss Adaptability and resilience in a fast-paced, rapidly scaling environment where priorities shift quickly and new challenges emerge regularly

Market Demand

High demand driven by explosive growth in quick commerce sector and critical need for operational optimization expertise in fast-scaling logistics operations

Important Skills

Critical Skills

SQL proficiency is absolutely essential as the foundation for all data extraction and analysis work, with daily use across multiple databases containing operational, customer, and performance data that drives business decisions Statistical testing methodologies are critical for validating operational improvements and ensuring that changes to logistics processes actually deliver measurable benefits rather than false positives Python and R expertise with data libraries forms the core technical foundation for advanced analytics, machine learning applications, and automated reporting systems that support rapid business scaling

Beneficial Skills

Machine learning and unstructured data experience becomes increasingly valuable as the company scales and seeks to implement more sophisticated predictive analytics and optimization algorithms Domain expertise in instant delivery or logistics operations provides crucial context for translating analytical insights into operationally feasible recommendations Consulting or operations experience offers important perspective on stakeholder management and business impact measurement that enhances the strategic value of analytical work

Unique Aspects

Opportunity to work at the intersection of traditional logistics optimization and cutting-edge quick commerce innovation, dealing with unique challenges like sub-hour delivery windows and micro-fulfillment center operations
Direct exposure to C-level strategic decision making through executive reporting and dashboard creation, providing unusual visibility into high-level business strategy for a mid-level role
Chance to influence operational strategy across multiple countries and cities simultaneously, gaining international business experience and cross-cultural operational insights
Access to substantial learning and development resources (€1,000 annual budget plus coaching) that demonstrates serious investment in employee growth and career advancement

Career Growth

Typically 18-36 months for progression to senior roles given the rapid growth environment and high learning curve in quick commerce analytics

Potential Next Roles

Senior Data Analyst or Lead Data Analyst roles within 18-24 months, with expanded team leadership responsibilities and strategic project ownership Data Science Manager positions focusing on logistics optimization and operational analytics within 2-3 years Head of Analytics or Director of Business Intelligence roles in quick commerce or logistics companies within 3-5 years Strategic consulting roles with major consulting firms specializing in logistics and supply chain optimization

Company Overview

Flink

Flink represents the leading edge of European quick commerce, having achieved remarkable growth from launch in February 2021 to operating in over 90 cities across Germany and the Netherlands, with revenues exceeding €400 million in 2022 and operational profitability. The company has secured backing from world-renowned investors including Prosus, Mubadala, Bond, DoorDash, and REWE, indicating strong market confidence and substantial resources for continued expansion.

Market leader in European quick commerce with strong competitive positioning against international players like Gorillas and Getir, demonstrating superior operational efficiency and sustainable business model execution
Dominant presence in German market with significant Netherlands operations, positioning employees at the center of European quick commerce innovation and expansion strategies
High-performance, growth-oriented culture with emphasis on operational excellence, data-driven decision making, and rapid iteration, typical of successful European tech scale-ups with strong diversity and inclusion commitments
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