Data Analyst (вакансія неактивна)

The ideal candidate for this position combines:
— strong technical knowledge, skills, and mathematical background
— deep understanding of SaaS business and the ability to do complete product and market analysis
— knowledge in product, and project management aspects
Skills to excel
At least 3 years of experience in data management and data analytics;
Proficiency in math, statistics, and probability theory;
Some experience with data science, machine learning, predictive modeling;
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;
Working knowledge of front-end and back-end technologies;

More than just a job
We help mass adoption of esports and unlocking a market for hundreds of millions of gamers and thousands of advertisers and sponsors, and you too can have an impact on this ride
Passionate, diverse, and supportive team members
Open, transparent, and bureaucracy-free company culture
Competitive remuneration.

Perform complex analytics requests;
Own the monitoring of business metrics, product/launch performance and proactively communicate findings to help the 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;
Manage and execute the process of A/B testing, implement best practices;
Design, implement, support and improve Data analytics solution which satisfies business needs;
Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale;
Conduct a 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);
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;