Collaborate with data scientists and software engineers to build new product features using machine learning, LLMs, and statistical techniques.
Drive high-impact projects from problem definition through metrics development, data extraction, model implementation, and presenting results to stakeholders.
Develop, deploy, and maintain machine learning models and pipelines at scale—including both batch and real-time applications.
Design and analyze experiments to measure the impact of new features or model changes.
Leverage deep dive statistical analyses to uncover actionable insights and inform critical tech and product decisions
Communicate your work clearly to engineering, product, and business stakeholders.
Requirements
At least 3 years of industry experience as a data scientist and Master’s (or PhD ) in a quantitative discipline such as Statistics, Economics or Engineering
Impact-driven: You’ve contributed to data science projects that made a real impact on live, customer-facing products — not just in theory, but in production.
Strong grasp of machine learning and statistical concepts and know how to choose the right model for the problem and make it work in a production environment.
Practical expertise in experimentation design and analysis.
Proficient in Python and SQL, and familiarity with software engineering principles around testing, code reviews, and deployment.
Clear communicator: You are comfortable explaining complex ideas and results to diverse audiences.
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