Senior Machine Learning Engineer

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Why us? Insurify is one of America's fastest-growing MIT FinTech startups and has been recognized as one of Inc. 5,000's fastest-growing private companies in America in 2025, 2024, 2023, 2022 and 2021, Forbes Fintech 50 List for 2023, 2022, and 2021, Forbes Next Billion Dollar Startups of 2022, and Top 100 InsurTech company. We're changing the way millions of people compare, buy and manage insurance with artificial intelligence, technology, and superior product design. Our company vision is to be recognized as the preeminent and most trusted digital agent for insurance comparison, purchase, and management. Our team is critical to achieving our vision and fostering the right culture is essential to our team's success. How you will make an impact Design, train, and iterate on ML models and algorithms that personalize the ranking of results within the product Identify opportunities for applying machine learning, propose experiments, and build models to improve customer conversion and engagement Take ownership of ML solutions end-to-end, from problem formulation and data exploration to model validation and iteration Collaborate with engineers and stakeholders using modern development practices such as version control (Git), code reviews, and reproducible experimentation Partner closely with the Marketing team to develop and improve machine-learning-driven bidding and targeting methodologies What you need to succeed 4+ years of relevant experience Experience building and using machine learning models with clear and measurable business impact Strong skills and hands-on experience in Python (numpy, pandas, sklearn, etc.) and SQL Comfortable working in production-oriented codebases, including using Git for version control An interactive and collaborative approach to delivering ML-powered data products Quick learning ability and a drive well-suited to a fast-paced startup environment Experience clarifying ambiguous business problems and translating them into effective ML solutions Curiosity about data, distributions, and outliers, with a strong interest in using data to propose and validate causes and effects Strong quantitative and programming skills paired with a product-driven sensibility Graduate degree in a technical or quantitative discipline Fluent in spoken and written English and Bulgarian

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