Alex Staff Agency

• Активный поиск и привлечение новых B2B-клиентов (мерчантов) в сегментах high-risk (adtech, gaming, adult, gambling, люкс, IT-сервисы). • Проведение полноценных переговоров с C-level и финансовыми директорами потенциальных партнеров. • Презентация решения по off-ramp криптопроцессингу, аргументация выгод сотрудничества. • Заключение контрактов и передача подписанных клиентов в аккаунтинг-отдел для дальнейшего сопровождения (модель «охотника»). • Выход на международные рынки с фокусом на крупные хабы (Кипр, Дубай, Лиссабон, Барселона, США).

Role Description Лицензированная платформа для off-ramp криптопроцессинга, работающая на рынке с 2011 года. Компания предоставляет B2B-услуги по переводу цифровых активов в фиат для глобальных мерчантов. - Активный поиск и привлечение новых B2B-клиентов (мерчантов) в сегментах high-risk (adtech, gaming, adult, gambling, люкс, IT-сервисы). - Проведение полноценных переговоров с C-level и финансовыми директорами потенциальных партнеров. - Презентация решения по off-ramp криптопроцессингу, аргументация выгод сотрудничества. - Заключение контрактов и передача подписанных клиентов в аккаунтинг-отдел для дальнейшего сопровождения (модель «охотника»). - Выход на международные рынки с фокусом на крупные хабы (Кипр, Дубай, Лиссабон, Барселона, США). Qualifications - Успешные B2B-продажи от 3-х лет в сфере крипто-процессинга, платежных систем или финтеха. - Свободное владение английским языком на уровне C1 (обязательно) для ведения переговоров с иностранными стейкхолдерами. - Глубокое понимание специфики high-risk вертикалей (adtech, gaming, adult, gambling). - Готовность работать полностью автономно, без длительного онбординга и плотного контроля. - Агрессивный «охотник», ориентированный исключительно на холодные продажи и привлечение новой клиентской базы. - Русский — C1/Родной (обязательно), Английский — C1 (обязательно). - Наличие действующей клиентской базы среди потенциальных мерчантов (бонусом). Requirements - Полностью удаленная работа. - Приоритетные локации для кандидатов — Кипр, Дубай, Лиссабон, Барселона, США. Benefits - Фиксированная часть: ~$2 000/мес (уровень варьируется в зависимости от локации кандидата). - Бонусная часть: 10% от маржи приведенных клиентов в первый год сотрудничества. - Символический процент от дохода клиента пожизненно после первого года работы. - Потенциальный доход (OTE): При закрытии 1–2 крупных клиентов в год доход составляет $150 000 – $300 000+. - Максимальная клиентская ставка (маржинальность): до €3 500. - Возможность масштабировать свое влияние на новые вертикали и географии в растущем бизнесе. Process Selection - Ознакомительное интервью. - Техническое интервью. - Финальное интервью (или сразу оффер). - Язык интервью: Русский (с обязательной проверкой уровня английского C1).

• We need someone who understands data deeply and uses Python to wrangle it — not a platform engineer, not a pure pipeline builder, but a data specialist who's comfortable with research, investigation, and the unglamorous work of making messy energy market data actually usable. • You'll spend significant time on tasks like: mapping BM units to power plants and fuel types, reconciling legacy data formats with current ones, ensuring consistency between different Elexon message types, and cleaning time-series data (outliers, gaps, overlaps). Some of this requires genuine investigation — cross-referencing sources, making judgment calls, documenting edge cases. There's no API that solves these problems for you. • Python is your primary tool (Pandas, Numpy, standard libraries) to minimise manual effort, but you should be comfortable that some detective work is unavoidable. If you find satisfaction in truly understanding a dataset's structure and quirks — rather than just piping data through and hoping for the best — this role is for you. **Data Mapping and Research** • Map BM units from Elexon to their corresponding power plants, substations, and fuel types — combining API data, public registers, and manual research • Map substations to ETYS zones and grid supply points • Build and maintain reference/master datasets that link identifiers across disparate sources (Elexon, National Grid ESO, TEC register, etc.) • Document mappings, assumptions, and known limitations clearly for downstream users **Data Reconciliation and Consistency** • Reconcile legacy data formats with current formats (e.g., historical operational data stored in different schemas or granularities) • Ensure consistency between different Elexon message types — understand the market data structure well enough to know why BOALF, BOD, and DISBSAD might not perfectly align and how to handle it • Investigate discrepancies between data sources and determine authoritative values **Data Cleaning and Quality** • Clean time-series data: detect outliers (price spikes, meter errors), fill gaps appropriately, resolve overlapping or duplicate timestamps • Develop reusable Python-based cleaning routines that can be applied across datasets • Understand why data quality issues occur (settlement reruns, late submissions, format changes) not just patch them **Pipeline Development (Supporting the Above)** • Write and maintain Python data grabbers for energy market APIs • Build dbt models to transform raw data into clean, analysis-ready datasets • Orchestrate workflows via GitHub Actions • Design PostgreSQL schemas that reflect your understanding of the domain

• Map BM units from Elexon to their corresponding power plants, substations, and fuel types — combining API data, public registers, and manual research • Map substations to ETYS zones and grid supply points • Build and maintain reference/master datasets that link identifiers across disparate sources (Elexon, National Grid ESO, TEC register, etc.) • Document mappings, assumptions, and known limitations clearly for downstream users • Reconcile legacy data formats with current formats (e.g., historical operational data stored in different schemas or granularities) • Ensure consistency between different Elexon message types — understand the market data structure well enough to know why BOALF, BOD, and DISBSAD might not perfectly align and how to handle it • Investigate discrepancies between data sources and determine authoritative values • Clean time-series data: detect outliers (price spikes, meter errors), fill gaps appropriately, resolve overlapping or duplicate timestamps • Develop reusable Python-based cleaning routines that can be applied across datasets • Write and maintain Python data grabbers for energy market APIs • Build dbt models to transform raw data into clean, analysis-ready datasets • Orchestrate workflows via GitHub Actions • Design PostgreSQL schemas that reflect your understanding of the domain

• Design, scale, and maintain real-time advertising bidding systems (DSPs, RTB Exchanges, and SSP platforms). • Optimize backend services using Java (Spring Boot / WebFlux) and Go (Golang) to meet strict low-latency SLA/SLO targets. • Build and manage data-intensive architectures utilizing high-load storage solutions (Aerospike, ClickHouse) and event-driven messaging (Apache Kafka). • Participate in R&D initiatives involving GenAI, integrating Agentic AI frameworks (LangChain, LangGraph, N8N) for workflow automation and predictive analytics. • Take full ownership of features end-to-end, contributing to the frontend layer (React / TypeScript) for internal tools and dashboards when required.

• Develop, refine, and calibrate rating algorithms, methodologies, and donate-weight normalization. • Build ratings across multiple dimensions: from global and regional scales to niche, highly professional segments. • Organize and automate data collection from external sources. • Design integrations to enrich our rating databases. • Translate product tasks into development—from raw requirements to fully functioning algorithms, data pipelines, and automation. • Implement and coordinate AI agents for data labeling, classification, and routine process automation.

Role Description The product is solving two fundamental problems of the modern information age: the lack of clear monetization for creators and broken navigation within the endless information noise. Core methodologies are already developed, and we have successfully launched ratings for movies, TV shows, and books. Now, we are looking for a Rating Production Lead to transform our existing developments into a scalable production system. In this role, it is essential to know how to work with algorithms, data, and process automation—including leveraging AI agents under the direct guidance of our CEO and CTO. - Develop, refine, and calibrate rating algorithms, methodologies, and donate-weight normalization. - Build ratings across multiple dimensions: from global and regional scales to niche, highly professional segments. - Organize and automate data collection from external sources. - Design integrations to enrich our rating databases. - Translate product tasks into development—from raw requirements to fully functioning algorithms, data pipelines, and automation. - Implement and coordinate AI agents for data labeling, classification, and routine process automation. Qualifications - Strong mathematical foundation in statistics, probability theory, graph theory, and ranking/scoring algorithms. - Preferred background: MSU, MIPT, HSE, SPbSU, ITMO, Bauman MSTU, or an equivalent level of rigorous academic preparation. (The degree itself is not a dealbreaker; what truly matters to us is your systemic understanding of data architecture). - Experience with databases, data architecture design, and proficiency in development tools like Python and SQL. - Proven track record of independently translating product requirements into mathematical models and production-ready code. - Clear understanding that AI is a practical tool for data processing and automation, not a magic wand. - Readiness to learn and master tools for working with AI agents and LLM integrations under the mentorship of our CTO. Requirements - Direct B2B contract up to $7,000 / month. - Fully remote with a flexible schedule. Geographically, we are looking for engineers based in Europe / CIS (outside of Russia and Belarus). - A strong Russian-speaking engineering department, but all company documentation is maintained in English. - A great opportunity to eventually step up into a Head of Department role and build your own team.

Role Description Это первый сезон литературной премии в память о детском писателе Валерии Михайловиче. Церемония награждения пройдёт в декабре 2026 года в одной из библиотек Москвы. Цель проекта — сохранить память автора, продолжать издавать и читать его книги. Нам нужен фандрайзер, который с нуля привлечёт спонсоров. У проекта нет готовых спонсорских материалов, нет базы партнёров, нет предыдущих сезонов. Вы будете сами создавать пакеты, презентации, вести переговоры и закрывать сделки. Это роль для самостоятельного специалиста, который не боится начинать с чистого листа. Задачи - Разработка спонсорских материалов с нуля (презентации, пакеты участия, коммерческие предложения). - Поиск и привлечение спонсоров: компании, бренды, фонды (без госструктур). - Проведение переговоров с потенциальными партнёрами. - Заключение договорённостей и сопровождение партнёров на всех этапах. - Развитие долгосрочных партнёрств (для следующих сезонов). - Самостоятельная постановка KPI и метрик (обсуждаем с оргкомитетом). - Взаимодействие с оргкомитетом (3 человека в Москве и Санкт-Петербурге). Qualifications - Опыт в фандрайзинге или B2B-привлечении спонсоров (культура, НКО, ивенты — будет плюсом). - Готовая база спонсоров — сильное преимущество (идеально: 2–3 партнёра по 200–300 тыс. рублей). - Умение самостоятельно упаковывать спонсорские предложения с нуля. - Навыки переговоров с ЛПР компаний и фондов. - Самомотивация, полная самостоятельность, готовность отвечать за результат. Requirements - Оплата: процент от фактически поступивших средств (размер обсуждается с подходящим кандидатом). Фиксированной части нет. - Оформление: ГПХ, самозанятость или ИП — на выбор. Юридически — обычная компания (не фонд). - Полная удалёнка, гибкий график. - Целевой бюджет: 3–6 млн рублей. - Дедлайн: 1 декабря 2026 года (к церемонии). - Сайт в разработке, приём заявок на премию: с 1 июня по 1 сентября.

• Own the Billing product area end-to-end: define vision, prioritise the backlog, write clear user stories and acceptance criteria, and ensure successful delivery of features. • Collaborate with Finance, Legal and Compliance to ensure billing solutions meet accounting standards, tax rules and regulatory requirements across relevant jurisdictions. • Partner with engineering and platform teams to design secure, resilient and scalable payment and invoicing systems, including support for multiple currencies, tax treatments, and payment providers. • Drive continuous improvement of billing operations: reduce manual reconciliation, improve cash collection, and automate dispute handling and refunds. • Work closely with Customer Success and Sales to understand commercial contracts, pricing models and invoicing needs; translate these into product capabilities that support new business models and market expansion. • Define and track KPIs for billing health and performance (e.g., DSO, failed payments, reconciliation rate) and use data to drive prioritisation. • Support migrations and integrations with external ERPs and accounting systems to ensure data integrity and smooth financial close processes. • Act as the product authority during planning, grooming and delivery ceremonies; communicate roadmap, trade-offs and release plans to stakeholders.

Role Description We need someone who understands data deeply and uses Python to wrangle it — not a platform engineer, not a pure pipeline builder, but a data specialist who's comfortable with research, investigation, and the unglamorous work of making messy energy market data actually usable. You'll spend significant time on tasks like: - Mapping BM units to power plants and fuel types - Reconciling legacy data formats with current ones - Ensuring consistency between different Elexon message types - Cleaning time-series data (outliers, gaps, overlaps) Some of this requires genuine investigation — cross-referencing sources, making judgment calls, documenting edge cases. There's no API that solves these problems for you. Python is your primary tool (Pandas, Numpy, standard libraries) to minimise manual effort, but you should be comfortable that some detective work is unavoidable. If you find satisfaction in truly understanding a dataset's structure and quirks — rather than just piping data through and hoping for the best — this role is for you. Qualifications - Strong Python skills for data work — fluent with pandas, comfortable writing clean, testable code, and can build reusable data processing logic. - Solid SQL skills — complex queries, window functions, CTEs in PostgreSQL. - Experience with messy, real-world data — reconciliation, cleaning, or mapping work. - Methodical and detail-oriented — notice inconsistencies and want to understand root causes. - Good documentation habits — understanding that undocumented mappings and assumptions are technical debt. - Self-directed — able to own ambiguous problems, do research, and communicate findings clearly. Requirements - Map BM units from Elexon to their corresponding power plants, substations, and fuel types. - Map substations to ETYS zones and grid supply points. - Build and maintain reference/master datasets that link identifiers across disparate sources. - Document mappings, assumptions, and known limitations clearly for downstream users. - Reconcile legacy data formats with current formats. - Ensure consistency between different Elexon message types. - Investigate discrepancies between data sources and determine authoritative values. - Clean time-series data: detect outliers, fill gaps appropriately, resolve overlapping or duplicate timestamps. - Develop reusable Python-based cleaning routines that can be applied across datasets. - Write and maintain Python data grabbers for energy market APIs. - Build dbt models to transform raw data into clean, analysis-ready datasets. - Orchestrate workflows via GitHub Actions. - Design PostgreSQL schemas that reflect your understanding of the domain. Benefits - Remote-first with async collaboration (Slack, GitHub, documented decisions). - Core overlap with UK business hours expected (at least 4 hours daily). - Competitive compensation based on location and experience. - Plenty of opportunities for learning and professional growth. - B2B contract with a paid vacation.