Эта вакансия в архиве

Посмотреть похожие вакансии ↓
Company hidden
обновлено 1 месяц назад

Middle Product Marketing Analyst (Fitness)

Формат работы
onsite
Тип работы
fulltime
Грейд
middle
Английский
b2

Описание вакансии

Текст:
/

TL;DR

Middle Product Marketing Analyst (Fitness): Analyzing product and marketing performance for a fitness app with an accent on experiment design, statistical analysis, and data-informed decision-making. Focus on optimizing user retention, churn analysis, and revenue strategies for subscription monetization.

Company

hirify.global is a company that develops a fitness app called FitMe for active individuals.

What you will do

  • Analyze product and marketing data for the FitMe fitness app.
  • Own full-cycle product and marketing analytics.
  • Independently prioritize analytical tasks and drive data-informed decisions.
  • Understand and optimize key metrics, user retention, churn, and revenue.
  • Design and evaluate experiments.
  • Collaborate with stakeholders to communicate insights.

Requirements

  • 2+ years of experience in a similar analytics role.
  • Advanced SQL proficiency for querying and analyzing large datasets.
  • Solid understanding of statistics, including experiment design, statistical tests, correlation analysis, and segmentation.
  • Hands-on experience with BI tools such as Tableau or Power BI.
  • Experience in full-cycle product analytics, owning both product and marketing analytics.
  • English: B2 required.

Nice to have

  • Python skills (pandas, data visualization, statistics) for data manipulation and analysis.
  • Experience with subscription monetization products (user retention, churn analysis, revenue optimization).
  • Basic knowledge of Data Science (machine learning concepts, predictive modeling, or clustering techniques).

Culture & Benefits

  • Opportunity to take ownership of analytics, drive initiatives, and make data-driven decisions.
  • Emphasis on excellent communication skills, clearly conveying insights and justifying decisions.
  • Attention to detail, ensuring accuracy in data analysis, reporting, and experiment evaluation.
  • Business-oriented thinking, understanding how analytics impacts product growth, user experience, and revenue.