- Company Name
- G-Research
- Job Title
- Machine Learning Researcher
- Job Description
-
**Job Title:**
Machine Learning Researcher
**Role Summary:**
Lead the development of cutting‑edge machine learning models for forecasting financial time series. Conduct research‑level experimentation, extend or innovate beyond standard industry methods, and translate findings into production‑ready solutions that measurably impact business performance.
**Expectations:**
- Deliver high‑impact, rigorously tested forecasting models.
- Publish and present results at top ML conferences.
- Drive methodological innovation within a data‑rich, compute‑intensive environment.
- Collaborate actively with peers in a vibrant research community.
**Key Responsibilities:**
- Research and design novel algorithms in deep learning, reinforcement learning, Bayesian methods, NLP, or approximate inference tailored to financial data.
- Experiment on large structured and unstructured datasets, evaluating model performance against benchmarks and business metrics.
- Prototype, implement, and iterate models using Python, NumPy, SciPy, Pandas, scikit‑learn, and Jupyter Notebooks.
- Manage end‑to‑end research workflow, including data ingestion, preprocessing, feature engineering, model training, and deployment pipelines.
- Contribute to the research platform, sharing tools, datasets, and best‑practice guides.
- Communicate findings through internal reports, whitepapers, and conference presentations.
**Required Skills:**
- Deep expertise in at least one of: deep learning, reinforcement learning, non‑convex optimisation, Bayesian non‑parametrics, NLP, approximate inference.
- Strong mathematical reasoning and ability to develop custom models.
- Proficient programming in Python; solid experience with NumPy, SciPy, Pandas, scikit‑learn, Jupyter.
- Object‑oriented design and code‑review discipline.
- Competence with large‑scale compute resources and version control.
- Ability to synthesize and apply the latest academic research.
- Kaggle or similar competition experience preferred.
**Required Education & Certifications:**
- Postgraduate degree (MSc/PhD) in machine learning, statistics, applied mathematics, computer science, or equivalent practical experience.
- Proven record of developing novel ML algorithms.
- Publication record in top conferences (NIPS, ICML, ICLR, ACL, etc.) highly desirable.
- Certifications or courses in advanced ML topics are a plus.