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bloomerang
Страна
США
Зарплата
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Product Analyst

Оценка ИИ

Отличная вакансия в стабильной SaaS-компании с прозрачной вилкой зарплаты и удаленным форматом. Сильный фокус на современные инструменты (AI, BigQuery) и социально значимую миссию компании повышают привлекательность.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует высокого уровня владения SQL и глубоких знаний в статистике (регрессии, временные ряды). Ожидается не просто выполнение задач, а проактивное управление бэклогом и использование AI-инструментов для масштабирования аналитики.

Анализ зарплаты

Медиана95 000 $
Рынок85 000 $ – 120 000 $
Оценка ИИ

Предлагаемая вилка $80k - $110k полностью соответствует рыночным стандартам для Product Analyst уровня Middle/Senior в США. Верхняя граница в $110k является конкурентной для компаний среднего размера в SaaS-секторе.

Сопроводительное письмо

I am writing to express my strong interest in the Product Analyst position at Bloomerang. With over four years of experience in SaaS product analytics, I have a proven track record of building the cohort studies and churn models that drive strategic product decisions. My expertise in SQL and advanced statistical methods, combined with a proactive approach to managing my own analytical backlog, aligns perfectly with the requirements of this role.

I am particularly drawn to Bloomerang’s mission-driven culture and your innovative approach to integrating AI into the analytical workflow. In my previous roles, I have successfully leveraged LLMs to accelerate exploratory data analysis while maintaining the statistical rigor necessary for defensible insights. I am eager to bring my experience in A/B testing, lifecycle monitoring, and stakeholder storytelling to help Bloomerang’s customers achieve even greater impact in the nonprofit sector.

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Откликнитесь в bloomerang уже сейчас

Присоединяйтесь к Bloomerang и используйте свои аналитические навыки, чтобы помочь некоммерческим организациям менять мир к лучшему!

Описание вакансии

At Bloomerang, we believe change happens on purpose. We champion the power and potential of nonprofits, igniting next-level impact with the team and technology built for purpose. Our powerful giving platform and stellar support enable tens of thousands of nonprofits to raise more, recruit more, and retain more, fueling maximum impact and raising the bar on what’s possible for the nonprofit sector. That's why, even as the nonprofit sector sees declines in giving, Bloomerang customers raise more year over year.

We're also in the business of creating thriving employees. Join a mission-driven culture built on our core values of Simplify, Care and Act. We know our people are the key to our success, and we're proud to be home to some of the most innovative and skilled individuals in the workforce today. Come feel invigorated and unstoppable with us!

The Role

As a Product Analyst at Bloomerang, you aren’t just transitioning into the field; you’re an experienced Analyst in the SaaS space. You’ve built thecohort studies, churn models, and A/B frameworks that Product Managers actually use to move the needle. You don't just take tickets—you manage your own backlog, select your own methodologies, and act as the proactive bridge between Product, Engineering, and Marketing. In an era where AI has democratized data exploration, your value is sharper than ever. You leverage AI to scale output and accelerate pattern recognition, but you provide the statistical rigor and human judgment those tools lack. You are the gatekeeper of truth—ensuring every insight is stress-tested, every experiment is designed correctly, and every piece of data reaching leadership reflects reality.

What You Will Do

  • Lifecycle Monitoring & Experimentation: Track and analyze core product metrics — usage, retention, activation, and revenue signals — to proactively surface trends and friction points before they reach stakeholder escalations. Design, execute, and analyze A/B tests and cohort studies, translating results into clear, evidence-backed product recommendations rather than inconclusive reports.
  • Predictive & Diagnostic Analytics: Apply regression analysis, significance testing, and time-series forecasting to go beyond descriptive reporting and into diagnostic and predictive territory — answering not just what happened, but why, and what’s likely next. Model forward-looking product trends including churn risk and customer lifetime value, with a standard for methodological rigor that makes results defensible to senior leadership.
  • User Sentiment & Competitive Intelligence: Synthesize qualitative signals — user interviews, NPS, support data, polls — with quantitative usage metrics to build a full-spectrum view of the customer experience, not just a metrics dashboard. Conduct competitive benchmarking to evaluate Bloomerang’s product positioning, identify feature gaps, and surface pricing and packaging opportunities.
  • Measurement Ownership & Data Integrity: Define measurement requirements for new features in partnership with Product — ensuring that success criteria, instrumentation, and baseline metrics are established before development begins, not retrofitted after launch. Maintain accountability for data quality and consistency across product datasets, proactively investigating upstream gaps and anomalies before they corrupt downstream conclusions.
  • AI-Augmented Analysis: Use AI assistants and LLMs as active tools in your analytical workflow to automate exploratory analysis, accelerate investigation, debug SQL logic, and surface non-obvious patterns at scale. Share AI prompts, reusable SQL snippets, and analytical templates with the broader team to multiply collective output — and apply critical judgment to AI-generated results to ensure they meet the same methodological bar as any other analysis.
  • Stakeholder Storytelling & Influence: Transform complex analytical findings into decision-ready narratives — visual, written, and verbal — that move product managers and cross-functional leads from curiosity to action. Practice guided persuasion: use data storytelling and curious questioning to align partners toward shared conclusions, build data literacy across teams, and influence product direction through evidence.

What You Need to Succeed

  • Analytical Experience: 3–5 years of hands-on experience working directly as a Product Analyst in a SaaS or technology company.
  • Technical Proficiency: Expert proficiency in SQL for complex data wrangling against large datasets (BigQuery preferred). Demonstrated ability to apply advanced statistical methods — regression, significance testing, time-series analysis — and to explain your methodology choices to technical and non-technical audiences.
  • Experimentation & Insight Generation: Proven experience analyzing A/B tests and cohort studies, translating statistically sound results into clear product recommendations. Track record of synthesizing qualitative and quantitative data sources into unified, compelling narratives.
  • Tools & AI Fluency: Proficiency with Business Intelligence and data visualization tools; Tableau and/or Looker experience preferred. Demonstrated fluency with AI-assisted analytical tools — LLMs, AI copilots, automation — as genuine productivity multipliers, with the critical judgment to validate and interrogate what’s produced.

Nice to Haves But Not Required

  • Hands-on experience prompting LLMs and AI tools for analytical tasks — writing queries, debugging logic, automating EDA, or generating data narratives.
  • Familiarity with data transformation tools such as DBT.
  • Experience with product event tracking and instrumentation tools (e.g., Pendo, Google Analytics, Segment).
  • Background in predictive modeling or exposure to ML frameworks beyond standard regression.
  • Experience in the nonprofit sector, fundraising technology, or donor management platforms.

Benefits

Health + Wellness

You’ll have access to generous health, vision, and dental insurance options as well as HealthiestYou, a healthcare service that offers convenient, confidential access to quality doctors 24/7, anytime, anywhere.

Time Off

You'll get a competitive PTO package that includes 20 PTO days, 3 flex days, 4 optional volunteer days, 12 paid holidays, as well as paid parental leave. More is more!

401kYou'll receive a 401k match to help invest in your future.

Equipment

Everything you need to be successful, shipped right to your door. You got this. We got you.

Compensation 

The salary range for this position is $80,000 - $110,000. You may also be eligible for a discretionary bonus. Actual compensation within the range will be dependent on your skills, experience, qualifications, and location, as well as applicable employment laws

Location

This is a permanent, full-time, fully remote position (within the U.S. and select Canadian Provinces only). Employees living in Indianapolis, IN are welcome to work from our company headquarters. We do not offer Visa sponsorship or relocation assistance at this time.

AccommodationsApplicants who require accommodations may contact careers@bloomerang.com to request an accommodation in completing an application.

Bloomerang is an Equal Opportunity Employer. Individuals seeking employment at Bloomerang are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.

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Навыки

  • Google Analytics
  • Tableau
  • A/B Testing
  • Python
  • LLM
  • SQL
  • Looker
  • dbt
  • BigQuery
  • Regression Analysis
  • Pendo
  • Segment
  • Time Series Analysis
  • SaaS Analytics

Возможные вопросы на собеседовании

Проверка навыков проведения экспериментов и понимания статистической значимости.

Расскажите о самом сложном A/B тесте, который вы анализировали. Какие метрики были ключевыми и как вы интерпретировали неоднозначные результаты?

Оценка способности работать с данными о потере клиентов, что критично для SaaS.

Как бы вы подошли к построению модели прогнозирования оттока (churn) для нашей платформы, учитывая специфику некоммерческого сектора?

Проверка технической грамотности и умения работать с большими данными.

Опишите ваш опыт работы с BigQuery. С какими самыми сложными SQL-запросами или проблемами оптимизации производительности вы сталкивались?

Оценка современного подхода к работе и умения использовать AI.

Как именно вы используете LLM или AI-ассистентов в своей повседневной аналитической работе, и как вы обеспечиваете валидность результатов, сгенерированных AI?

Проверка навыков коммуникации и влияния на продукт.

Приведите пример, когда ваши аналитические выводы противоречили мнению менеджера по продукту. Как вы доносили свою позицию и к какому решению в итоге пришли?

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bloomerang
Страна
США
Зарплата
80 000 $ – 110 000 $