Position: Data analytics Lead
Company: Data Science UA
Experience required: 5y
English level: intermediate

Job purpose
Your primary focus will be working with the on-chain and off-chain data to address the most common use cases that our clients face. For example, building dashboards that help optimize marketing spending by having a clear understanding of user acquisition and retention. Or profiling users or measuring product metrics. Finding more use cases that could be standardized is also part of the story. You will be working directly with the clients to understand the business problem and the best way to bring value.

Duties and Responsibilities
- Data analysis, pipeline implementation, and dashboards creation based on typical and custom dapps data
- Contribute to the product concept planning from a data analyst perspective, and help drive platform development from the user’s standpoint
- Direct communication with clients to identify and solve business problems
- Help data engineers to establish the right data aggregation pipelines and DB structure

Requirements
- Master’s Degree in a quantitative field (Math, Statistics, Computer Science, Engineering, Data Science, Operations Research, etc.)
- Ability to effectively communicate in written documents and oral briefings regarding studies initiation, justification of methods selected, results, conclusions, and recommendations.
- Understanding blockchain industry concepts is highly valued.
- Experience in setting up an analytical function from scratch, hiring and leading other analysts is highly appreciated.
- English intermediate strong level or higher

Competent in:
- Applied Statistics (Exploratory Data Analysis and Distributions Fitting, 
- Inference on Populations, Regression Analysis, Causality)
- Experience with popular BI tools
- Good understanding of visualization techniques
- Databases (SQL and NoSQL)

Basic knowledge in:
- Development Tools (SVN, Git)
- Python programming skills
- Understanding of software development company functioning
- Understanding of software development life cycles

Nice to have:
- Data Mining concepts (Clustering, Frequent Pattern Mining, Outliers Detection)
- Predictive analytics (Classification and Regression Models, Time-series analysis and forecasting, Survival or duration analysis as a plus)
- Design of the predictive research
- Machine Learning Concepts (Supervised/Unsupervised learning, Models assessment, and comparison)
- Machine Learning Algorithms (Tree-based models, Linear Models, Instance-based models, etc.)

Benefits
☝️ A chance to build the future of web3 user analytics from scratch and work with the strongest web3 ecosystem projects
💻 The newest equipment if you need it
📌 Courses, conferences, and other self-development activities upon request
🌴 Paid 18 days off (can be negotiable)
👨‍💻 Fully remote work or hybrid
🌱 Equity