Machine Learning & Quantitative Researcher
About Bilby
Bilby combines data analytics, machine learning, and advanced generative AI techniques to analyse government data at scale and extract predictive signals. Our mission is to enhance decision-making by providing early insights into policy changes. We are a small team of experts in political analysis, technology, and the hard sciences.
Why Join Bilby?
- Fast-paced research and methodical iteration: Your work will be a combination of delivering v0 models quickly, and building tools to iterate to more refined solutions.
- High autonomy: You will have creative control both over (1) How to frame the technical problems underlying business challenges, and (2) How to solve these problems.
- High Impact: Your work will directly influence clients’ understanding of regulatory shifts and policy changes.
- Small, focussed, collaborative Environment: Join a tight-knit team that values learning, knowledge-sharing, and collective success.
About the Role
We are seeking an ML and Quantitative Researcher with 3+ years of experience in applying data analysis, machine learning, and generative AI for predictive modelling. The ideal candidate will also have a background in the hard sciences and familiarity with quantitative or algorithmic trading strategies.
Key Responsibilities
- Model Development:
- Build, train, and iterate on predictive models at speed and scale.
- Suggest and integrate additional data sources to improve model performance.
- Collaborate on building a scalable training pipeline with robust metrics.
- Model Assessment:
- Evaluate model quality, conduct error analysis, and refine approaches.
- Align model outputs with Bilby’s business goals and client needs.
- Quantitative Research:
- (Preferred) Develop and backtest quantitative strategies or trading models.
- Collaboration & Communication:
- Work closely with cross-functional teams, including data engineering and product.
- Communicate complex findings to technical and non-technical stakeholders.
- Ensure notebook/code handoffs are clean and well-documented for the engineering team.
Required Skills & Qualifications
- Academic Background: Degree in a hard science (e.g., Physics, Mathematics, Computer Science, Engineering).
- ML & AI Expertise:
- 3+ years in data analysis, machine learning, and/or generative AI.
- Strong understanding of model architectures (e.g., transformers for NLP).
- Programming & Tools:
- Proficiency in Python and libraries/frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Familiarity with data processing tools (e.g., Pandas, NumPy).
- Experience with version control (Git).
- Experience with numerical programming in python.
- Analytical & Cognitive Skills:
- Proven problem-solving and critical-thinking abilities.
- Strong analytical mindset with attention to detail.
- Experience with statistical analysis.
Nice-to-Have Skills
- Quant/Trading: Experience in designing and backtesting trading models.
- MLOps: Familiarity with production pipelines, containerisation (Docker), CI/CD, and cloud platforms (AWS, GCP, or Azure).
- NLP: Knowledge of Hugging Face or other NLP libraries for large-scale text analysis.
How to Apply
If you’re excited about harnessing AI and quantitative methods to drive predictive insights in government policy, we’d love to hear from you. Please hit the apply button
