13 дней назад
Sales Operations Analyst
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Sales Operations Analyst (SQL/Python/AI): Building sales analytics, experimentation, dashboards, territory-planning models, commission systems, and forecasting tools with an accent on data quality, revenue analytics, and incentive design. Focus on simulating account coverage and lead routing, automating forecast root-cause analysis, and validating complex metrics across application, DWH, and BI layers.
Location: Bulgaria; remote initially, transitioning to a hybrid format after the physical office opens in Sofia
Company
operates a digital marketplace that connects manufacturers with buyers and provides access to global manufacturing capacity.
What you will do
- Define analytical problems, success metrics, hypotheses, and experiments with Sales and Marketing stakeholders.
- Build and maintain Looker dashboards, validate data quality, and collaborate with the data warehouse team on marts and metrics.
- Investigate data discrepancies across ERP and application systems, source data, the data warehouse, reporting layers, and BI dashboards.
- Design account-tiering, coverage, territory, staffing, lead-routing, and go-to-market prioritization models.
- Model commission plans, quota attainment, payout logic, pipeline KPIs, conversion rates, and representative performance trends.
- Develop sales forecasting systems and automate root-cause analysis for monthly, quarterly, and annual forecast fluctuations.
Requirements
- Bachelor’s or Master’s degree in Data Science, Computer Science, IT, Engineering, or a related field.
- 3+ years of experience in analytics or data science, ideally in B2B or B2C marketplaces.
- Strong SQL and Python skills with dashboarding experience in Looker, Tableau, Qlik, or a similar tool.
- Knowledge of probability, statistics, hypothesis testing, confidence intervals, power analysis, A/B testing, regression, and time-series analysis.
- Daily practical use of AI coding assistants and LLMs for analysis, automation, and prototyping, with the ability to verify AI output.
- Fluent English is required; Russian is a plus.
Nice to have
- Applied machine learning experience, including supervised and unsupervised learning, feature engineering, model evaluation, and cross-validation.
- Understanding of data warehouse design, data structures, and ETL/ELT.
- Experience with adjacent areas such as entrepreneurship, business administration, product, UX, machine learning, or psychology.
Culture & Benefits
- Full-time employment contract with remote work at the beginning and a future hybrid format.
- Work laptop and corporate English lessons.
- Structured onboarding covering processes, technology, and systems.
- Flexible processes, planning, and a collaborative environment.
- Well-being activities, charity projects, and development opportunities.
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