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Machine Learning Specialist
| Company | CAIS |
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| Location | New York, NY, USA |
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| Salary | $180000 – $230000 |
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| Type | Full-Time |
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| Degrees | Master’s |
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| Experience Level | Senior |
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Requirements
- Proven expertise in Python programming, with deep knowledge of data structures and algorithms.
- Excellent command over statistical reasoning.
- In-depth understanding of predictive modeling techniques, time series analysis, anomaly detection, and clustering.
- Proficiency with data visualization, statistical modeling and data analysis frameworks such as scikit-learn, SciPy and matplotlib.
- Hands-on experience with Pytorch and deep learning model architectures, such as Transformers, VAE, state space and diffusion models.
- Experience in fine tuning models using LoRA or similar methods.
- Experience in model testing, optimization and feature engineering, with the ability to source and integrate diverse data sets to improve performance.
- Cloud deployment expertise, including Kubernetes, Docker and/or cloud ML platforms such as Amazon SageMaker.
- Exceptional attention to code quality and emphasis on adhering to established software design patterns.
- 4+ years of hands-on experience developing and deploying production-grade ML models in one or more of the above areas.
- MS in Mathematics, Statistics, Data Science, Physics or a related quantitative field.
Responsibilities
- Develop models leveraging features sourced from structured and unstructured data.
- Design and develop models for portfolio optimization, recommendation systems, propensity models, lead scoring, time series forecasting, and risk analysis using a combination of classical statistical methods, machine learning algorithms and novel deep learning algorithms.
- Write modular, production-grade code for model development, data pipelines, and deployment. Prototype user demos rapidly to gather stakeholder feedback and iterate on solutions.
- Build scalable systems to evaluate, calibrate and iteratively evolve the models in response to changing economic and investment conditions.
- Ensure rigorous testing with carefully crafted end-to-end and unit test cases for models and related sub-components.
- Prepare structured and unstructured data to use as features for maximum model performance.
- Deploy and monitor models in a cloud environment, prioritizing scalability, low latency, and A/B testing methodologies.
- Stay at the forefront of AI advancements, continuously researching and applying the latest in deep learning and machine learning techniques.
Preferred Qualifications
- Experience in the financial services industry, specifically investment management, is a huge plus.
- 5 years of professional experience in workplace setting.
