Senior Data Scientist / Senior ML Engineer

About the Role
You will lead the design, development, and deployment of ML/AI/GenAI models that power core products (e.g., pricing, personalization, fraud detection). You’ll collaborate with Data Engineers, Product Managers, and Platform teams to deliver production-grade models that have a real impact.

What Will You Do

• Own end-to-end ML model lifecycle: problem framing, data exploration, training, deployment, monitoring.
• Design and develop scalable solutions using classical ML and GenAI techniques.
• Implement MLOps best practices: versioning, reproducibility, monitoring, CI/CD for models.
• Collaborate with squads and platform teams to ensure reusability and adherence to standards.
• Mentor junior ML engineers and contribute to the internal ML knowledge base.
• Integrate models with APIs and backend services as needed.
• Embrace and enforce a "you build it, you run it" approach, owning the full lifecycle of ML models from development through monitoring and continuous improvement.

What Are We Looking For

• 5+ years’ experience in applied ML, AI, or data science.
• Strong proficiency in Python and ML/AI libraries (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, HuggingFace Transformers).
• Experience with MLOps tools (e.g., MLflow, SageMaker) and managing versioning, testing, and observability.
• Deep understanding of model development workflows including feature engineering, hyperparameter tuning, model evaluation, and A/B testing.
• Deep understanding of statistical modeling, statistical inference, and the appropriate application of statistical tests (e.g., t-test, chi-square, ANOVA, regression analysis); ability to interpret results and communicate implications to both technical and non-technical audiences.
• Proven track record of deploying ML models in production at scale.
• Knowledge of ML best practices including bias mitigation, explainability (e.g., SHAP, LIME), and model monitoring for drift and fairness.
• Strong understanding of data pipelines, experimentation, and model evaluation.
• Familiarity working in a cloud-native environment (AWS preferred) with CI/CD, GitOps, and IaC tools (e.g., Terraform, CDK).
• Hands-on experience with GenAI / LLM integration (e.g., RAG, fine-tuning, embeddings, prompt engineering) and tools such as LangChain, LangGraph, or LlamaIndex.

What We Offer You

• An inclusive and diverse culture that encourages innovation.
• Highly competitive compensation packages, including bonuses and the potential for shares.
• Prioritization of personal development with regular training and an annual learning stipend to tackle new challenges and grow your career in a hyper-growth environment.
• Opportunity to join a talented team of over 30 nationalities working in 14 countries, gaining valuable experience in an exciting industry.
• Autonomy, mentoring, and challenging goals that create incredible opportunities for both you and the company.