About the role

Senior Engineering Manager overseeing Data Science & Data Engineering teams at Xsolla. Focused on innovation in data infrastructure and ad tech for smarter decision-making.

Responsibilities

Lead and grow a high-performing, distributed team of data scientists, ML engineers, and data platform engineers
Define and execute the data science and ad tech roadmap, advancing initiatives in user modeling, campaign optimization, targeting, and personalization
Architect and manage ML pipelines and experimentation frameworks, including feature engineering, training pipelines, model serving, A/B testing, and causal inference systems
Oversee real-time pipelines for ad events (e.g., impressions, clicks, conversions), enabling responsive attribution and performance optimization
Collaborate with Product, Growth, and Marketing to develop audience scoring, LTV/churn models, and incrementality testing for media measurement and bidding efficiency
Ensure scalable, privacy-compliant data infrastructure aligned with GDPR, CCPA, and ATT, including support for SKAdNetwork, CMPs, and identity frameworks
Foster engineering excellence with a focus on reproducibility, model evaluation, observability, and model lifecycle management
Drive a strong feedback loop between experimentation and business outcomes, translating data science insights into product and go-to-market wins
Mentor engineers and scientists on career development, technical depth, and cross-functional leadership

5+ years of experience in software/data engineering or applied data science
3+ years managing technical teams in ML, analytics, or ad tech domains
Deep understanding of machine learning and statistical modeling, including regression, classification, causal inference, uplift modeling, and forecasting
Hands-on experience with ML/data platforms such as Snowflake, BigQuery, Spark, Airflow, dbt, MLFlow, and feature stores
Proven experience in architecting and deploying end-to-end ML systems into production (batch and real-time)
Knowledge of ad tech ecosystems, including campaign hierarchies, attribution models (multi-touch, view-through), and creative performance tracking
Familiarity with audience management, segmentation, and personalization frameworks in programmatic or CRM marketing
Experience with privacy-preserving measurement, including support for SKAdNetwork, GAID/IDFA deprecation, and consent systems
Bachelor’s or Master’s in Computer Science, Engineering, Statistics, or a related field
PhD is a plus

medical, dental, and vision
PTO
a personalized career roadmap for each employee
investing in professional development through training and educational opportunities