Machine Learning Specialist

CAIS is the pioneer in democratizing access to and education about alternative investments for independent financial advisors, empowering them to engage and transact with leading asset managers on a massive scale through a wide variety of alternative investment products and technology solutions. CAIS provides financial advisors with a broad selection of alternative investment strategies, including hedge funds, private equity, private credit, real estate, digital assets, and structured notes.

CAIS also delivers industry-leading technology, operational efficiency, and world-class client service throughout the pre-trade, trade, and post-trade experience. CAIS supports over 50,000 advisors who oversee more than $6 trillion in network assets.

As a Machine Learning Specialist / Data Scientist, you will play a pivotal role in shaping the future of predictive modeling within the alternative asset management and wealth management space. Yourexpertisewill influence product vision discussions, drive data-informed decisions, and enhance the intelligence of our platform.

You’ll collaborate across teams to develop scalable, robust models and frameworks for adoption across products that empower financial advisors and asset managers to navigate complex markets with confidence.

• 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.

• 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, Sci Py and matplotlib.
• Hands‑on experience with PyTorch and deep learning model architectures, such as Transformers, VAE, statespace 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 Sage Maker.
• 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.
• Experience in the financial services industry, specifically investment management, is a huge plus.
• MS in Mathematics, Statistics, Data Science, Physics or a related quantitative field.
• 5 years of professional experience in workplace setting.

CAIS is consistently recognized as a Best Place to Work, and our culture is at the heart of our success. We are committed to fostering an inclusive environment where employees can be their most authentic selves and feel inspired and supported to bring their voice forward to drive community, growth, and innovation. We are an equal opportunity employer, and do not discriminate on the basis of any protected attribute, including…