Position: Data Scientist
Company: DMarket
Experience required: 3y
English level: intermediate

Responsibilities: 

- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
- Forecasting of sales, turnover, margin, revenue, LTV, CAC, ROMI (ARMA/ARIMA models, etc.)
- Assortment and stock management (ABC/XYZ analysis, ordering, tracking and controlling, prediction algorithms, automation, creation of recommendation system)
- Planning, forecasting, launching, and analyzing of efficiency of promotions (different promo mechanics)
- Analysis of elasticity and creation of algorithms to achieve KPIs
- Price optimization, automation and market analysis
- Customer segmentation (RFM, HVC, LTV, CAC, similar audience models, etc.)
- Marketing Mix Modeling
- Develop company A/B testing framework and test model quality.
- Prototyping of machine learning algorithms (neural networks, decision trees, support vector machines, linear regression, dimension reduction)
- Data preprocessing, feature engineering, models training and prediction accuracy check
- Build, test, and deploy custom ML/AI models and algorithms, and develop processes for monitoring and analyzing their performance in production environments

Requirements: 
- 3+ years of commercial experience, experience with Python/R (statistical and ML packages)
- Advanced knowledge of higher mathematics, probability theory, statistics, calculus
- Excellent theoretical knowledge and hands-on experience in Machine Learning and Deep Learning
- Expert knowledge in SQL/NoSQL (PostgreSQL, MySQL, MariaDB, MongoDB, etc.)
- Knowledge and experience in statistical and data mining techniques: GLM/Regression, random forest, boosting, trees, text mining, social network analysis, etc.
- Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, recommendation system, etc.
- Experience analyzing data from 3rd party providers: Google Analytics, Google Ads, Facebook Insights, etc.