Data Analyst
Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Nov 13, 2026.
About the Company
Our client is part of a large international holding company that has been operating in the market for over 25 years. Over this time, the company has built strong expertise in developing digital products - web platforms and mobile applications.
The mobile app division has been actively growing for the past three years, while the Health & Wellness team was formed just a few months ago. Currently, the company is building a dedicated ecosystem of health and wellbeing products. The plan for the upcoming year is to launch up to 10 applications, but the main focus right now is on two products: an affirmations app and a rewarded step tracker that incentivizes users for physical activity.
The team works exclusively for the US market. Both products are available on Android and are ad-monetized, with no subscription model. The primary goal is to prepare the products for active scaling and reach an advertising budget of around $300K per month.
Role Objective
To develop the ecosystem's products through in-depth analytics, experimentation, and machine learning.
Responsibilities
- Drive the global data strategy in alignment with business objectives.
- Ensure data quality, reliability, and accessibility across all teams.
- Oversee the design, development, and maintenance of data infrastructure (data pipelines, cloud solutions, monitoring).
- Foster a strong data-driven culture that enables decision-making based on reliable analytical insights.
- Manage high-impact analytical and data science projects (LTV forecasting, fraud detection, personalization, A/B testing).
- Place AI at the center of product development and team operations by developing AI-based features, automation, and internal agents to accelerate results and create new user experiences.
- 5+ years of experience in Data Analytics / Business Intelligence,
- Deep knowledge of Advanced SQL (complex queries for distributed datasets), Python or R for modeling and automation, BI tools (Tableau, Looker, Power BI), as well as modern approaches to DWH and analytics engineering (dbt),
- Experience with mobile app analytics (subscription model and ad monetization), LTV and revenue forecasting, designing database schemas, and building UML diagrams,
- English level C1 or higher.