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Konstantinos KattidisKK

Konstantinos Kattidis

Head of Data &Analytics

€800/day
Berlin, DE
8-15 years

Average response time: 1 hour

About Konstantinos

As a seasoned Data & Analytics leader with over a decade of experience, I help companies transform their data into growth. I’ve built and led high-impact analytics teams across fintech, e-commerce, and Web3, including roles at Zalando and P2P.org delivering data platforms, reporting ecosystems, and AI-driven insights that support strategic decisions and real-time operations.

I specialize in building end-to-end data infrastructures (dbt, BigQuery, Airflow), BI dashboards (Looker, Superset, Power BI), and data analytics / data science AI solutions that enable fast, confident decision-making and automation. I’ve helped scale startups, drive investor reporting, optimize validator performance, and launch client-facing data products—unlocking millions in added revenue and efficiency.

I’m now focused on supporting startups, scaleups, and product teams that want to operationalize data, boost performance, and build a modern analytics foundation. If you’re looking for someone who can translate business goals into measurable, data-backed outcomes, let’s talk.
  • English

    Native or bilingual

  • Greek

    Native or bilingual

Can work on-site
Berlin (up to 40km)

Experience

  • P2P.org
    Head of Data &Analytics
    April 2024 - October 2025 (1 year and 6 months)
    Berlin, Germany
    - Built and led the end-to-end Data & Analytics organization (data engineering + BI) across Product, Finance, Operations,
    Sales, and Marketing, unifying fragmented data sources into a single analytics function and mentoring a team of 9+
    FTEs. Embedded data-driven decision-making across all GTM and product initiatives.
    - Boosted validator APR from 12% to 16% across three blockchains, generating ~€90K additional MRR through custom
    optimization algorithms.
    - Reduced financial reporting cycle from 15 days to 1 day by building company-wide data marts and real-time revenue
    dashboards, creating a single source of truth for KPIs.
    - Increased institutional client engagement by 30% through the launch of external-facing data products, including a
    real-time staking data API and performance dashboards.
    - Strengthened data governance and quality management frameworks, implementing GDPR-aligned MDM and data
    lineage to prepare the organization for IPO readiness.
    - Tech stack: GCP, BigQuery, dbt, Airflow, Apache Superset, incident.io, Grafana, Metaplane
    AI and Advanced Analytics Business intelligence Data analysis SQL SQL
  • Zalando
    (Acting) Head of Analytics – Platform Experience, Merchant Performance, Pricing
    January 2023 - April 2024 (1 year and 3 months)
    Berlin, Germany
    - Scaled the analytics function across 9 business units, aligning Product, Merchant, Finance, and Operations with
    company strategy, while leading and mentoring a cross-functional team of 9 FTEs to deliver high-impact insights..
    - Cut merchant pricing-related complaints by 64% by leading the development of a pricing misconduct detection model
    that flagged and reduced unfair pricing practices.
    - Enabled smarter investment decisions by building foundational LTV models for Zalando Direct, driving optimized
    resource allocation, promotional spend, and proactive merchant retention strategies.
    - Lowered product return rates by ~3 pp through an optimized size chart algorithm, validated via rigorous A/B testing.
    Tech stack: AWS, Python, SQL, Databricks, MLflow, Datalab, Collibra, Superset, Looker Studio, MicroStrategy.
    Python SQL Team management KPIs and Metric Definition and Monitoring Experimentation
  • Zalando
    Team Lead, Performance &Analytics
    October 2020 - January 2023 (2 years and 3 months)
    Berlin, Germany
    - Built and scaled Zalando Direct’s analytics function by hiring and mentoring 5 analysts, while defining roadmaps and
    priorities aligned with strategic objectives to embed data into product and commercial decisions.
    - Reduced customer service contacts by 4pp and increased checkout conversion by 0.2% by developing an ML model to
    predict delivery windows for merchant-shipped products.
    - Improved merchant retention by 3% and cut intervention lead time by 2 weeks by creating predictive models that flagged
    at-risk merchants through behavioral and revenue signals.
    SQL Business intelligence AI and Advanced Analytics KPIs and Metric Definition and Monitoring A/B Testing

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Education

  • Master of Science (MSc)
    University of Warwick
    2015
    Master of Science (MSc)
  • B.Sc.
    Cyprus University of Technology
    2014
    B.Sc.

Skill set

Categories