Data Scientist (Pricing)

- Engage with the business objectives behind key tasks: pricing for B2B/B2C, forecasting and optimization of financial and operational metrics, incident prioritization, and improving customer journey efficiency (revenue growth, cost savings, business impact).
- Drive ML projects end-to-end: from problem definition and formalization to modeling, piloting, and presenting results.
- Collaborate with data engineers to collect the necessary datasets and assess implementation feasibility.
- Work with analysts on A/B test design: defining metrics, splits, and interpreting results.
- Develop models (classic ML and DL, time series, uplift modeling), conduct error analysis and performance evaluation.
- Prepare models and code for transfer to production infrastructure (deployment and releases handled by the technical team).
- Take ownership of model quality, monitor key metrics, and collaborate with the team on degradation issues and improvement plans.