About

About me

About me

Paul Buchholz

Data & Marketing Consultant

Professor of Data Science for Marketing — SKEMA Business School


Paul Buchholz


Data Scientist & Business Consultant – E-commerce & Marketing

Professor Python for Digital Marketing – SKEMA Business School

Turning data into decisions. And decisions into results.

Who I am

Bridging data, business, and education.

I started my career on the business side, in environments where performance, KPIs, and customer impact mattered more than isolated numbers.


Today, I combine this business culture with advanced data science expertise to help companies turn their data into clear, actionable marketing decisions.

Alongside my consulting work, I teach data and AI applied to marketing at SKEMA Business School, with a constant goal: making data understandable, useful, and actionable.

What I do

I support companies when decisions need to be made: what to prioritize, what to fix, and where to invest.

  • Clarify complex and ambiguous marketing situations

  • Structure a reliable and decision-oriented data reading

  • Support marketing decisions over time with an external perspective

My philosophy

Data should serve people, not the other way around.

Numbers only matter when they help us understand behavior, tell a story, and guide smarter actions.


That’s why I focus on:

Clarity

Actionable insights

Actionable insights

Collaboration

Data has no value on its own.
It only becomes powerful when it is understood, shared, and applied.

My Journey

2018 – Technical rigor & problem-solving foundations

2020 – Master’s in Business Engineering (KEDGE BS)

2021 – Business Manager @ Capgemini & Generix Group

2023 – Transition to Data Science

2025 – Today: Consulting & Teaching

Demanding industrial environments (engineering, design).


Built rigor, structure, and complex problem-solving skills.


This methodological foundation still shapes my data approach today.

Formalization of business challenges: strategy, performance, value creation.


Key realization: every business decision is a data decision.


Clear connection between analysis, strategy, and decision-making.

Led complex, multi-country projects.


Translated business challenges into concrete actions.


Built KPIs designed to support decisions, not decoration.

Advanced training in Python, analytics, and modeling.


Applied data science to marketing and e-commerce use cases.


Specialization: data-driven marketing performance.

Supporting companies on acquisition, conversion, and profitability.


Structuring analytics systems and marketing decisions.


Teaching Data & AI applied to marketing at SKEMA Business School.

My Journey

2018 – Engineering as a foundation for discipline

2020 – Master’s in Business Engineering (KEDGE BS)

2021 – Business Manager
@ Capgemini & Generix Group

2023 – Transition to Data Science

2025 – Today: Consulting & Teaching

Demanding industrial environments (engineering, design).
Built rigor, structure, and complex problem-solving skills.

This methodological foundation still shapes my data approach today.

Formalization of business challenges: strategy, performance, value creation.

Key realization: every business decision is a data decision.
Clear connection between analysis, strategy, and decision-making.

Led complex, multi-country projects.

Translated business challenges into concrete actions.
Built KPIs designed to support decisions, not decoration.

Advanced training in Python, analytics, and modeling.
Applied data science to marketing and e-commerce use cases.
Specialization: data-driven marketing performance.

Supporting companies on acquisition, conversion, and profitability.

Structuring analytics systems and marketing decisions.
Teaching Data & AI applied to marketing at SKEMA Business School.

My Journey

2018 – L’ingénierie comme socle de rigueur

2020 – Master en Business Engineering (KEDGE BS)

2021 – Business Manager
@ Capgemini & Generix Group

2023 – Transition vers la Data Science

2025 – Aujourd'hui : Consulting et Enseignement

Demanding industrial environments (engineering, design).
Built rigor, structure, and complex problem-solving skills.

This methodological foundation still shapes my data approach today.

Formalization of business challenges: strategy, performance, value creation.

Key realization: every business decision is a data decision.
Clear connection between analysis, strategy, and decision-making.

Led complex, multi-country projects.

Translated business challenges into concrete actions.
Built KPIs designed to support decisions, not decoration.

Advanced training in Python, analytics, and modeling.
Applied data science to marketing and e-commerce use cases.
Specialization: data-driven marketing performance.

Supporting companies on acquisition, conversion, and profitability.

Structuring analytics systems and marketing decisions.
Teaching Data & AI applied to marketing at SKEMA Business School.

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