ABOUT COMPANY

SoftServe Business Systems was founded in 2003. We aim high; our mission is to lead the digital revolution in the FMCG industry. It means delivering the best products & services possible that empower businesses to grow and improve efficiency.

We are a product company, and this affects our day-to-day activities. Our team is highly involved in the client’s needs, we value business expertise, and we take every step with extra carefulness. Among our clients are businesses like AB InBev, Unilever, JDE, PepsiCo, Henkel, and others.

SoftServe Business System’s ideal candidate can share the company’s values and become a reliable partner for the team.

REQUIREMENTS

Strong analytical skills, high attention to detail, and a systematic approach to working with large volumes of structured and repetitive dataConfident Excel user (filters, formulas, structured tables; Power Query is a plus)Good visual perception to compare products, designs, and packaging detailsExperience with product catalogs, datasets, or structured content is a plusClear written communication skills to request and clarify information with clientsResponsible, attentive, patient, and consistent; able to maintain quality in repetitive tasks and take ownership of assigned workCalm, focused, and willing to learn and deepen understanding of the product and domainBasic understanding of retail shelf layout principles is a plusStrong Intermediate+ level of English for both spoken and written communication with clientsExperience with FMCG products, retail audits, or shelf analytics (nice to have)Familiarity with image-based analysis, product recognition workflows, or work with ambiguous or incomplete data (would be a plus)

RESPONSIBILITIES

Processing, analyzing, and maintaining large volumes of structured product data with high accuracy and attention to detailWorking with Excel files (filters, formulas, structured tables) to validate, update, and organize datasetsComparing products, designs, and packaging details to identify differences, inconsistencies, and errorsEnsuring data quality and consistency across product catalogs and related materialsFollowing defined rules, patterns, and workflows when performing repetitive data tasksCommunicating clearly in writing with clients or internal stakeholders to request, clarify, and confirm missing or unclear informationApplying basic retail shelf layout principles when reviewing or organizing product dataTaking ownership of assigned tasks, meeting deadlines, and maintaining consistent output qualityLearning project-specific guidelines, product details, and domain knowledge to continuously improve performance