Senior Data Scientist

Madgicx is transforming how eCommerce brands scale their advertising through AI-powered automation and intelligent optimization. We empower thousands of global brands to make smarter marketing decisions, automate complex workflows, and unlock next-level ROAS with cutting-edge data and machine learning technologies.

As we expand our AI ecosystem, we're looking for a Senior Data Scientist who wants to build production-ready ML systems—not just experiments—and directly influence the future of autonomous advertising.

As a Senior Data Scientist at Madgicx, you will architect, train, deploy, and monitor machine learning models that operate at massive scale. You'll take ownership of end-to-end ML systems—from feature pipelines and experimentation to real-time inference powering multi-agent decision-making across billions of ad impressions.

You'll work closely with engineering, product, and data teams to ship AI solutions that classify creatives, identify high-value audiences, optimize campaigns in near-real time, and drive measurable business outcomes.

If you enjoy combining research-level thinking with production-grade engineering, this role offers full ownership, real impact, and unique datasets you won't find anywhere else.

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• Architect and deploy high-performance ML pipelines capable of serving predictions in under 100ms.
• Build and maintain feature engineering pipelines for messy, high-volume advertising data.
• Develop and ship deep learning models, graph-based systems, and tensor-based representations.
• Implement real-time model serving for multi-agent orchestration and automated campaign optimization.
  Own the full ML lifecycle: experimentation training validation A/B testing- production.
• Build monitoring systems to detect model drift, data issues, and performance degradation.
• Collaborate with engineering teams to design API-first ML architectures that integrate seamlessly into the Madgicx platform.
• Apply causal inference, statistical modeling, and forecasting to uncover real performance drivers.
• Ensure models are explainable, reproducible, and aligned with product and business requirements.

• 5+ years of experience deploying ML models in production.
• Advanced degree (MS/PhD) in a quantitative field.
• Strong Python skills (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow).
• Hands-on experience with scalable ML systems, model serving, and ML monitoring.
• Experience designing and integrating ML models into API-first architectures.
• Solid understanding of deep learning, forecasting, experimentation, and feature engineering.
• Practical experience with graph-based models, tensor operations, causal inference, and time-series modelling.
• Strong MLOps fundamentals (versioning, reproducibility, model lifecycle management).

• Experience with large-scale advertising or marketing data.
• Familiarity with real-time inference and low-latency systems.
• Background in multi-agent systems or reinforcement learning.

An engineering-first Data Scientist who ships production models, writes clean and reliable code, and takes full ownership of the end-to-end ML lifecycle.

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• Unlimited Time-Off Policy — flexible rest when you need it.
• Annual Performance Review — structured feedback, career development, and compensation review.
• Real product impact: Your models will influence billions in annual ad spend across thousands of brands.
• Technical ownership: Full autonomy over ML systems from research to production.
• Modern stack & datasets: Access to massive advertising datasets and significant compute resources.
• Learning & growth: Budget for courses, conferences, certifications, and research time.
• Remote-first culture: Flexible hours, high trust, and global team collaboration.
• Competitive compensation including equity and performance-based bonuses.