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fundamental

fundamental - Data Scientist - Extensions

Europe+ Equity4d ago
In OfficeSeniorEMEAArtificial IntelligenceData AnalyticsData ScientistPythonscikit-learnXGBoostPandasNumPyKagglePolarsONNXDocumentation

Requirements

• 5+ years of experience in data science or machine learning roles • Strong Python skills, including fluency with pandas, numpy, and scikit-learn • Deep hands-on experience with traditional ML models: XGBoost, LightGBM, CatBoost, and similar gradient boosting frameworks • Solid understanding of what makes real-world tabular data challenging: class imbalance, high cardinality, distribution shift, missing values, and more • Strong experimental mindset - comfortable designing benchmarks and drawing rigorous conclusions from noisy results • Ability to work autonomously and drive work from idea to shipped output • Familiarity with tabular foundation models (TabPFN, CARTE, or similar) • Competitive data science experience (Kaggle, DrivenData, or similar) - especially top finishes on tabular competitions • Background in a domain where structured prediction matters: finance, supply chain, healthcare, retail, or industrial • Experience contributing to or designing internal ML libraries or shared tooling • Familiarity with DuckDB, Polars, or modern in-process analytics engines • Comfort reading ML research papers and translating findings into practical implementations

Responsibilities

• Research and develop data science methods that improve NEXUS predictive performance across diverse enterprise datasets, industries, and prediction task types • Design and implement robust, production-quality Python components with a strong focus on correctness, generality, and reusability • Deeply understand the characteristics of real-world enterprise data and develop strategies that help NEXUS handle them reliably • Run rigorous experiments to measure the impact of new approaches, design meaningful benchmarks, and use results to guide prioritization • Work across a wide variety of structured data problems - including but not limited to classification, regression, ranking, and forecasting • Collaborate closely with the Engineering and Research teams to develop a deep understanding of NEXUS model behavior and use that knowledge to inform your work • Work with Applied AI Engineers to validate approaches on real customer datasets and translate findings into product capabilities • Contribute to technical documentation and internal best practices, helping the broader team apply new capabilities correctly and confidently

Benefits

• Competitive compensation with salary and equity • Comprehensive health coverage for you and your dependents • Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys • Relocation support for employees moving to join the team in one of our office locations • A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action

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