Назад
6 дней назад

Middle Business Analyst (AI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
Belarus
hhВакансия с HeadHunter. Контакт ведёт на hh.ru

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Описание вакансии

Текст:
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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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