CanadaEngineering Manager, Data
1 г. назад
120k–160k CAD / yearCanadaWorldwideLeadRemote
machine learningdata engineeringml systemsdata infrastructurerecommendation enginesfeature engineeringmodel deployment
Lead a team of data engineers, ML engineers, and data scientists delivering recommendation engines, personalization systems, and data infrastructure for a global gaming platform.
О компании
- ABOUT YOU You are a strategic and hands-on Engineering Manager with deep expertise in data platforms and machine learning systems. You will lead a distributed team of data engineers, ML engineers, and data scientists delivering the recommendation engines, personalization systems, and data infrastructure that power products used by millions of players worldwide. The ideal candidate is a collaborative leader with strong technical foundations and a proven track record of shipping end-to-end ML systems into production. You hold the bar high for what gets shipped: reliable pipelines, reproducible models, thoughtful feature engineering, and observability built in from the start. You know how to connect model performance to real business outcomes, and you bring a low-ego, people-first appr
Обязанности
- 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.
Требования
- 5+ years of experience in software/data engineering or applied data science, with 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.
- Excellent leadership, communication, and stakeholder management skills across technical and non-technical audiences.
- Bachelor’s or Master’s in Computer Science, Engineering, Statistics, or a related field. PhD is a plus.