Senior Data Scientist
Who We Are
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.
About the Role
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.
What you will be doing
- 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.
What you will bring to the table
Must-Have
- 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).
Nice to Have
- 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.
Who We’re Looking For
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.
What we offer you
- 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.
Join us in revolutionizing the world of online advertising
