В роли сочетаются аналитика данных и работа с клиентами, но широкий круг задач, аутсорсинговый формат и неуказанная зарплата затрудняют оценку условий.
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Широкий круг задачЗарплата не указанаАутсорсинговая компанияВостребованная аналитика
Оценка от Hirify AI
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Текст:
Hirify AI/Оригинал
TL;DR
Middle Business Analyst (AI): Turning customer and business requirements into clear tasks, validating data, and building dashboards and reports with an accent on SQL, business analysis, data quality, and customer-facing analytics. Focus on investigating anomalies, clarifying ambiguous requirements, supporting onboarding and demos, and using AI tools to improve analysis and documentation.
Location: Hybrid work in Minsk, Belarus; office address: 33/2 Matusevicha Street
Company
QA and IT services provider delivering end-to-end quality assurance, testing, security auditing, and distributed-team coordination for enterprise projects.
What you will do
Gather and clarify business requirements and translate them into clear engineering tasks.
Validate customer data, perform QA/QC, and investigate the root causes of anomalies and data issues.
Build dashboards, reports, KPIs, and executive summaries using customer data.
Support customer onboarding, product demonstrations, meetings, and customer success activities.
Investigate customer requests and unexpected system behavior.
Use AI tools to improve analysis and documentation efficiency.
Requirements
4–8+ years of experience as a Data, Business, Product, or Solution Analyst.
Degree in a quantitative field such as data analytics, statistics, mathematics, computer science, engineering, or economics.
Strong SQL, Excel, and Tableau and/or Power BI skills.
Knowledge of statistics, regression, forecasting, and data quality metrics.
Experience working directly with customers and stakeholders, owning initiatives end to end, and delivering measurable business impact.
Excellent spoken and written English and the ability to work independently in a fast-paced environment.
Nice to have
Experience in energy, trading, risk management, or financial services.
Customer-facing analytics experience in enterprise SaaS.
Python, machine learning, AI/LLM, predictive analytics, or simulation-model experience.
Understanding of R², RMSE, MAE, MAPE, confidence intervals, and correlation.
Culture & Benefits
Full-time hybrid work arrangement.
Customer-centric delivery focused on satisfaction and risk mitigation.
Work across pre-project services, acceptance testing, IT security auditing, and distributed-team coordination.
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