We are seeking a highly skilled Senior Data Scientist to join our dynamic AI team. The ideal candidate blends a strong foundation in machine learning, statistics, and software engineering with a passion for modern, AI-accelerated development. You will be responsible for leading the research, design, and end-to-end development of cutting-edge machine learning systems at scale.
What you'll be doing:
Innovate at Scale: Design and deploy advanced ML solutions by leveraging our vast, large-scale datasets.
Build & Scale: Develop online, scalable models and tools using machine learning, deep learning, NLP, and modern LLM frameworks.
End-to-End Ownership: Drive projects through their entire lifecycle-from translating complex business questions into technical strategies, all the way to robust production deployment.
Production Excellence: Champion high engineering standards by building, monitoring, and optimizing resilient production workflows.
Cross-Functional Collaboration: Work closely alongside data scientists, ML engineers, product managers, analysts, and developers to solve complex, multi-faceted problems.
What you'll be doing:
Innovate at Scale: Design and deploy advanced ML solutions by leveraging our vast, large-scale datasets.
Build & Scale: Develop online, scalable models and tools using machine learning, deep learning, NLP, and modern LLM frameworks.
End-to-End Ownership: Drive projects through their entire lifecycle-from translating complex business questions into technical strategies, all the way to robust production deployment.
Production Excellence: Champion high engineering standards by building, monitoring, and optimizing resilient production workflows.
Cross-Functional Collaboration: Work closely alongside data scientists, ML engineers, product managers, analysts, and developers to solve complex, multi-faceted problems.
Requirements:
Education: MSc or PhD in Data Science, Computer Science, Mathematics, Statistics, or a related engineering field.
Experience: 4+ years of proven experience as a Data Scientist solving complex business problems with state-of-the-art algorithms.
Deep Learning: Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
Engineering & Production: High-level software engineering expertise, with a strong track record of deploying, maintaining, and scaling models in rigorous production environments.
Strong analytical thinking: Take a vague business question, translate it into a testable hypothesis, build the infrastructure to run an experiment, and draw rigorous conclusions from the results.
Massive Scale: Experience working with billions of records and big-data frameworks (e.g., Spark, Ray, Dask, Airflow).
Domain Expertise: Proven experience building and optimizing applied recommendation systems.
AI development: Fluency with modern AI coding tools and practices (e.g. Cursor, Claude Code, Copilot) and an eagerness to integrate them into your daily workflow
Leadership & Soft Skills: Demonstrated experience leading machine learning projects. You are a highly analytical team player capable of handling multiple tasks simultaneously in a fast-paced environment.
You might also have:
LLM & Agentic Frameworks: Experience building applications with modern AI tools and frameworks (e.g., LangChain, LangGraph).
AI Observability: Hands-on experience with LLM observability, evaluation, and tracing frameworks (e.g., Langfuse).
MLOps & Infra: Experience working with MLOps tools (e.g., MLflow, Kubeflow, Weights & Biases, SageMaker) and feature stores (e.g., Feast, Tecton).
Education: MSc or PhD in Data Science, Computer Science, Mathematics, Statistics, or a related engineering field.
Experience: 4+ years of proven experience as a Data Scientist solving complex business problems with state-of-the-art algorithms.
Deep Learning: Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
Engineering & Production: High-level software engineering expertise, with a strong track record of deploying, maintaining, and scaling models in rigorous production environments.
Strong analytical thinking: Take a vague business question, translate it into a testable hypothesis, build the infrastructure to run an experiment, and draw rigorous conclusions from the results.
Massive Scale: Experience working with billions of records and big-data frameworks (e.g., Spark, Ray, Dask, Airflow).
Domain Expertise: Proven experience building and optimizing applied recommendation systems.
AI development: Fluency with modern AI coding tools and practices (e.g. Cursor, Claude Code, Copilot) and an eagerness to integrate them into your daily workflow
Leadership & Soft Skills: Demonstrated experience leading machine learning projects. You are a highly analytical team player capable of handling multiple tasks simultaneously in a fast-paced environment.
You might also have:
LLM & Agentic Frameworks: Experience building applications with modern AI tools and frameworks (e.g., LangChain, LangGraph).
AI Observability: Hands-on experience with LLM observability, evaluation, and tracing frameworks (e.g., Langfuse).
MLOps & Infra: Experience working with MLOps tools (e.g., MLflow, Kubeflow, Weights & Biases, SageMaker) and feature stores (e.g., Feast, Tecton).
This position is open to all candidates.
