tldr: analysts, T-Bank, ~400–700k/month gross + annual bonuses, office, hybrid, remote, Moscow/Saint Petersburg

The team is currently growing actively, so we are looking for middle+ and above DA / DS / MLE for the T-Bank Travel Efficiency team.

We create and implement algorithms that improve the economics of the Travel business: helping to grow GMV and profit through cashback, pricing, promotions, recommendations, and experiments.

Main areas:

1. Dynamic pricing and cashback in Travel Determine who, for what, and how much cashback / discount to give, in order to grow revenue without margin decline. Transition from heuristics to uplift models, causal approaches, optimization, and ML algorithms together with the product and ML team.

2. Marketing budget optimization Develop MMM, attribution models, and causal approaches to evaluate channel incrementality. Understand the real contribution of marketing to growth and reallocate budgets to points with maximum ROI.

3. Search for new Travel growth drivers Generate hypotheses based on product data, research, and experiments, lead the creation of new mechanics, and bring the best solutions to production.

We expect from the candidate:

• solid SQL and Python skills;
• good knowledge of mathematical statistics and the ability to apply it to real tasks;
• understanding of ML at least at the level of basic principles;
• strong product and business logic;
• a desire not only to analyze but also to influence decisions.

Will be a plus:

• experience in uplift modeling / causal inference;
• experience in implementing ML models into production;
• familiarity with discrete optimization;
• experience in efficiency, advertising, recommendation, pricing, or Travel teams.

If you are interested or have questions - write to @baushkiner, I will tell you more.