Job Title: Data Analyst / Repricing Analyst | Remote

Location: Eastern Europe, CIS, and the Balkans

Salary: $1,300-$1,700/month gross
Schedule: Full-time, 40 hours/week (Strong overlap with Madrid working hours. Minimum 4-5 hours of overlap.)

Only English CVs will be accepted.

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Our Client:

Our client is a dynamic worldwide retailer dedicated to bridging the gap in global markets. They specialize in identifying and sourcing high-demand products that are either physically unavailable or prohibitively expensive in specific regions.

By leveraging a sophisticated global supply chain, they ensure that consumers have access to the goods they need at competitive prices. Their mission is to democratize product availability, making unique and essential items accessible to customers regardless of their geographic location.

With a lean, fully remote team of 30 people spread across 4 continents, they operate with a global mindset from the ground up. They believe in enabling their people to live their best lives, whether that means building healthy habits, traveling the world, or accelerating their careers.

In This Role, You’ll:

Turn numbers into daily pricing and stock decisions in a fast-moving e-commerce environment. This role is built for someone who is genuinely strong with numbers: running calculations, working with margin logic and forecasts, and finding the relationships and discrepancies hidden in data. Direct repricing experience isn't required. Strong members of our client's pricing team come from finance, data analytics, and even programming backgrounds, because the commercial side can be learned on the job, while strong quantitative skills are the foundation.

This is not about matching competitor prices. It's about calculating the right price for each product based on demand, stock, margin, competition, and timing, then measuring whether that call was right.

You'll work daily with product-level data, competitor context, stock dynamics, sales performance, seasonality, and margin logic, turning multiple moving signals into clear, structured decisions. The nature of the work is close to trading on the stock market: you play against the market and your competitors, forecast demand, make daily calls under uncertainty, measure outcomes, and keep learning from what worked and what didn't. It also shares a lot with financial analysis and planning (FP&A).

What You'll Be Doing

Daily Marketplace & Pricing Decisions: Own daily pricing decisions for an assigned portfolio, applying the company's pricing framework based on performance, stock, and market signals.
Product & Market Analysis & Forecasting: Analyze product performance, demand, and competitor behavior, and forecast how price changes will affect sales volume and margin.
Stock Direction & Replenishment Signals: Assess demand and stock availability to guide replenishment and stock protection priorities.
Inventory Flow & Availability: Support inventory allocation and movement decisions to connect stock availability with pricing and sales.
Commercial Data & Marketplace Dynamics: Work with product-level commercial data to identify patterns, risks, and opportunities across the portfolio.
AI-Assisted Decision Workflow: Review AI-generated pricing and stock suggestions, validating or challenging them based on commercial judgment.
Decision Documentation & Quality: Document key decisions with clear notes on the signal, action, and rationale.
Continuous Improvement: Help refine the pricing and stock decision process by flagging recurring patterns and edge cases.

What You’ll Bring:

Experience Level

We are looking for someone with 2–5 years of experience in an analytical, commercial, financial, marketplace, trading, pricing, category, or product-related role.
English C1

Must-Have Skills & Abilities

Strong Numerical Skills: This is the core of the role. Confident with calculations, percentages, margin math, and forecasting, and able to connect multiple signals into one practical, cause-and-effect conclusion.
Analytical Thinking: Able to find relationships, patterns, and discrepancies in data, and to back conclusions with numbers rather than intuition alone.
Optimization Under Uncertainty: Able to weigh trade-offs and make sound decisions with incomplete information; familiarity with optimization, probability, or inventory logic is a plus.
Commercial Sense: Understands, or is quick to learn, how price, demand, availability, competition, and timing drive business outcomes, and can turn that into daily decisions with real impact.
Marketplace / Market Sense: Curious about competitive dynamics and quick to notice shifts in demand, competitors, or seasonality.
Spreadsheet Fluency: Strong Excel/Sheets skills, comfortable with messy data and building simple analyses independently.
Written Reasoning: Explains reasoning clearly and writes structured notes (signal → action → rationale).
Working Style: Structured, proactive, and calm when decisions need to be made without full certainty.
Open to feedback, clear in communication, and comfortable using AI tools as support for reasoning and analysis.
Motivation & Initiative: Genuinely curious about data and markets, with a clear reason for wanting to grow in analytics and pricing, and the initiative to own a portfolio rather than wait for instructions.

Relevant Backgrounds

Data / Analytics Backgrounds (Data Analyst, BI Analyst, Reporting Analyst, analysts with SQL, Python, or programming experience)
Finance / Economics / Planning Backgrounds (Financial Analyst, FP&A / Financial Planning & Forecasting Analyst, Controller, Economist / Business Economist, Unit Economics / Profitability Analyst)
Trading / Market-Oriented Backgrounds (Trading / Market Analyst, Quant or Risk Analyst, Yield / Pricing Analyst)
Quantitative Education (degree in Mathematics, Statistics, Economics, Finance, Physics, Engineering, Computer Science, or a similar field)
Commercial / Marketplace / Product Backgrounds (Marketplace / E-commerce Analyst, Pricing Analyst, Business Analyst with commercial exposure, Revenue / Growth Analyst, Category Management Analyst, Assortment / Merchandise Analyst)

Strong Plus / Nice-to-Have Experience

SQL or Python for data exploration.
Forecasting, financial modeling, or statistical analysis experience.
Trading, pricing, revenue management, or marketplace performance experience.
Experience making decisions where outcomes were measured against targets, benchmarks, or financial results.
Experience working with SKU-level performance, demand, margin, product positioning, or competitor dynamics.
Experience working with seasonality, promotions, stock planning, replenishment logic, competitor monitoring, category performance, unit economics, or inventory allocation.
Any repricing or marketplace exposure (Amazon, Walmart, Ozon, Wildberries, eBay, Shopify, or similar) is a bonus, not a requirement.
Regular use of AI tools such as ChatGPT or Claude for reasoning and analysis.

What’s In It for You:

Competitive salary: $1,300 to $1,700 USD per month.
Flexible working hours
Full-time permanent contract
Paid vacation (22 working days + 14 banking holidays)
Direct impact as you work directly affects pricing, margin, sales performance, stock availability, and product positioning.
Direct exposure - you will work directly with the COO and CEO.
Tech-forward environment within a modern AI-supported workflow.
Growth path: Potential to grow into deeper pricing, marketplace, category, stock, or commercial ownership.
Full remote-first setup with European working hours.