When fashion retailers' strategic pricing decisions depend on accurate data, rigorous analysis, and impactful guidance, you make it happen. As Markmi's Data Scientist - Pricing Optimization, you're the analytical expert who guides enterprise fashion retailers through this new paradigm of AI-enabled markdown optimization. You'll combine data science with hands-on consulting to help merchandising teams make confident, data-driven pricing decisions.
In 2024 we released Markmi, a pricing platform for fashion retail that enables merchandising teams to make smarter, faster, and more profitable pricing (markdown) decisions.
By leveraging fashion-focused intelligence and advanced forecasting, Markmi enables teams to set optimal price markdowns that swiftly respond to market shifts, protect margins, and drive revenue, all without relying on outdated spreadsheets or generic tools. Our algorithms, trained specifically on fashion data, empower retailers to reduce manual workload, gain better control over the markdown process, and achieve superior sales outcomes.
As a Data Scientist - Pricing Optimization, you're the analytical powerhouse behind our customers' success. You partner with our Customer Success Manager (who handles relationships) while you own the technical expertise.
This is a consulting role with serious analytical depth. You'll work directly with enterprise fashion retailers, investigating their data, explaining what our algorithms recommend and why, guiding them to make confident pricing decisions, then tracking results and adjusting approaches as needed. Think of yourself as part data scientist, part pricing strategist, part trusted advisor.
You will work side by side with our Customer Success Manager, Product Manager and Engineering team. Together, you will ensure that issues are resolved quickly and insights flow back into development.
The Role
Primary Responsibilities (Pricing Optimization & Customer Consulting):
Own technical onboarding: Validate data quality, assist in the first configuration of business rules and constraints, train customers on the platform, and ensure the first optimization runs deliver strong, credible results
Investigate and resolve technical issues: Act as first-line technical escalation, running SQL queries to diagnose customer-reported problems and validate data accuracy
Partner with merchandising teams: Analyze their markdown challenges, explain what the algorithms recommend and why, and advise on how to calibrate scenarios for their specific market context
Present to leadership: Help explain optimization scenarios to merchandising directors and leadership, quantifying trade-offs (margin vs. sell-through, aggressive vs. conservative markdowns) in business terms
Build and maintain a knowledge base: Create SQL snippets, analysis templates, and internal tools to improve the efficiency of our processes
Feed back insights: Share recurring technical issues and customer insights with the Product Manager to inform the product roadmap, and collaborate with the Algorithm Engineer to identify potential improvements to the algorithms.
Secondary Responsibilities (Pre-Sales Support):
Support the GTM team with technical expertise during pre-sales, including customer demos and showcasing best practices
What We're Looking For
Must-Have:
Strong SQL skills; comfortable working with relational databases
2+ years in a customer-facing data science role: Data scientist, advanced analytics consultant, pricing analyst, or similar. You know how to extract insights from data AND communicate them effectively to business stakeholders
Consulting mindset: You thrive in client-facing situations, translating analytical findings into clear business recommendations that drive action
Strong analytical and problem-solving skills with a pragmatic mindset
Excellent communication skills: Can present technical findings to non-technical stakeholders (merchandising managers, directors) with clarity and confidence
Ownership mentality: Ability to take ownership of customer issues and follow through until resolution
Comfortable in a startup environment: Dynamic SaaS setting with high-touch enterprise clients and evolving processes
Bonus:
Experience with data onboarding, ETL processes, or data validation
Scripting ability in Python to automate recurring tasks
Familiarity with BI tools or data visualization
Experience working in retail, fashion, or pricing-related industries
Understanding of pricing or merchandising concepts (markdowns, elasticity, sell-through, margin management)
Exposure to customer success in a SaaS company
Statistics or optimization background (elasticity modeling, forecasting, recommendation algorithms)
Why Join Markmi?
This isn't your typical data science role. You won't be isolated in Jupyter notebooks tweaking models at will. You'll work directly with Europe's leading fashion retailers, partnering with a Customer Success Manager and supported by our algorithm and product teams. Your analyses and guidance will help merchandising teams navigate the next phase of fashion retail, one where AI-driven pricing means higher margins, less waste, and smarter decisions in a rapidly evolving industry.
Join a growing team of passionate professionals building a cutting-edge, AI-enabled solution with a modern tech stack. Working from our Ghent office, you'll be immersed in a dynamic, innovation-focused environment where great ideas come to life.
Our office sits in the heart of Ghent with excellent connections by car, train, or (e-)bike, and plenty of spots nearby to relax after work. We provide a competitive salary package with comprehensive benefits, including an optional company car and fuel card, bike plan, hospitalization insurance, plus your laptop and smartphone.
Beyond the day-to-day, we invest in our team culture through regular company trips, organized events, and impromptu get-togethers that bring everyone together. We're committed to creating a collaborative environment where you can grow, connect with colleagues, and do your best work.
Up for the Challenge?
If you're excited to become the analytical advisor helping fashion retailers navigate AI-driven pricing optimization, we'd love to hear from you.
Apply now and we'll review your resume and may invite you for an initial phone interview. You'll then tackle a job-specific challenge and present your solutions. Impress us, and you could be the next key addition to our team in Ghent!
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