Job Description
- Job Description:
- Identify predictive patterns in alternative textual and tabular data sources
- Mine time‑series and cross‑sectional relationships in high‑frequency and daily tabular data
- Build and compare NLP architectures (transformers, embeddings, topic & sentiment models)
- Develop statistical and machine‑learning models (linear factor, tree‑based, gradient boosting, neural nets) that combine text‑derived features with numeric factors
- Construct robust, transaction‑cost‑aware back‑tests
- Partner with Data Engineering to scale data pipelines and feature stores
- Work with Portfolio Engineering to integrate signals into systematic strategies and monitor live performance
- Present findings to senior leadership; contribute to Stormlight’s research culture through white‑papers, internal talks, and code reviews
- Requirements:
- Education – M.S. or Ph.D. in Computer Science, Statistics, Physics, Electrical Engineering, Applied Math, or a related quantitative field
- Programming – Expert‑level Python (pandas, NumPy, PyTorch or TensorFlow, scikit‑learn); solid SQL; version control (git)
- NLP & ML – Hands‑on experience training and fine‑tuning large language models, embeddings, and classical NLP pipelines; strong grasp of supervised learning, regularization, cross‑validation, and hyper‑parameter optimization
- Data Handling – Comfort manipulating TB‑scale datasets; proficiency with Spark, Dask, or comparable distributed frameworks
- Research Rigor – Track record of designing repeatable experiments, performing thorough statistical validation, and communicating uncertainty
- Communication – Ability to translate complex technical concepts into clear, actionable insights for stakeholders
- Benefits:
- Bonus based on performance
- Flexible schedule
- Home office stipend
- Opportunity for advancement
- Paid time off
- Profit sharing
- Signing bonus
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