Our company is looking for an experienced Product Analyst who is able to manage the whole process of A/B testing and will become our expert on business metrics, insights and large-scale data analysis in a complex product. The ideal candidate for this position is able to do complete product and market analysis and outline critical information for each stakeholder, including CPO, CEO and Product Managers.

Skills to excel:

•3+ years of experience in data management and data analytics;

•Proficiency in math, statistics, and probability theory;

•Strong systemic and algorithmic thinking;

•Experience with SQL and schema-design;

•Experience with ETL tools;

•Knowledge of A/B testing concepts and tools;

•Experience with BI tools: Google Data Studio/ Microsoft PowerBI / Tableau etc.

•Experience in building Data Warehouse;

•Strong data modeling skills;

•Strong data munging/processing skills;

•Solid professional experience using Python for purposes of model development model implementation in production;

•Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications;

•Understanding of ML/DS algorithms is a plus.

What you'll do:

•Manage and execute the process of A/B testing, implement best practices;

•Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale;

•Conduct fast search for data-driven insights;

•Provide result interpretations;

•Conduct large-scale data analysis to make business recommendations (e.g. what-if, cost-benefit, impact analysis);

•Own the monitoring of business metrics, product/launch performance and proactively communicate findings to help business focus on key decisions to improve products and services;

•Present findings and recommendations to multiple levels of stakeholders, by creating visualizations of quantitative information;

•Work with engineering teams to develop new data measurement to aid in understanding product’s usage;

•Perform exploratory data analysis to find product improvement features that can drive additional value for users;

•Perform complex analytics requests.