Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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В Company hidden можно напрямую влиять на продукт в растущем секторе чистой энергетики, а сочетание аналитической инженерии и количественных задач выглядит цельным; при этом детали условий остаются неясными из-за работы в офисе и отсутствия информации о компенсации.
?Широкий профиль
Современный стек
Климатические технологии
Влияние на продукт
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Analytics/ML Engineer - Data Team (SQL/dbt and Machine Learning): Building data models, metrics, and a semantic layer for self-service analytics across the customer journey with an accent on analytics engineering, statistics, optimization, and machine learning. Focus on defining product KPIs, solving complex quantitative problems, and improving clean energy products and processes with experimentation, physical models, and telemetry data.
Location: Stockholm, Sweden; Stockholm HQ
Company
hirify.global is a clean energy-tech company developing heat pumps, solar power, and battery storage solutions to reduce residential emissions and energy costs, with headquarters in Stockholm and operations across Europe.
What you will do
Build and maintain data models and metrics using SQL and dbt.
Define KPIs with Product teams, track performance, and identify improvement opportunities.
Develop the semantic layer powering self-service analytics across the customer journey.
Apply statistics, experimentation, optimization, and machine learning to improve products and processes.
Use AI-assisted tools such as Claude in daily work.
Requirements
3+ years of experience in analytics engineering, data science, machine learning, or a similar quantitative role.
Strong SQL skills and experience working with large datasets.
Experience with data transformation and dimensional data modeling.
Strong analytical and problem-solving skills, including the ability to tackle problems without obvious solutions.
Interest in understanding the business and working closely with Product teams to improve how things work.
Nice to have
Quantitative background in mathematics, physics, engineering, statistics, or a related field.
Experience developing or deploying machine learning models.
Experience with statistical modeling, experimentation, or causal analysis.
Experience with optimization problems, physical models, or time-series and telemetry data.
Familiarity with cloud data platforms such as GCP, AWS, or Azure.
Culture & Benefits
Work closely with decisions shaping the customer journey and directly influence product development and market growth.
Work across analytics engineering, statistics, data science, machine learning, and real-world physical systems.
Collaborate with Product teams and diverse teams across international markets.
Join a fast-growing scale-up with a supportive, inclusive, entrepreneurial, and solution-oriented culture.
Access career advancement and personal and professional growth opportunities.
Work from the brand-new Stockholm office at Norra Stationsgatan 93, near public transport.
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