# Data Scientist - Extensions

**Company:** [Fundamental Research Labs](https://hotfix.jobs/companies/fundamental-research-labs)
**Location:** Remote
**Role:** Data Science
**Experience:** 5+ years
**Skills:** Python, pandas, NumPy, scikit-learn, Xgboost, Lightgbm, Catboost, Tabpfn, Duckdb, Polars
**Posted:** 2026-06-22

> Research and develop data science methods to enhance NEXUS tabular model performance across enterprise datasets. Design production-grade Python components and run rigorous experiments to improve prediction on real-world structured data.

## Job Description

## Key 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

## Must Have
- 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

## Nice to Have
- 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

## 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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