Machine Learning Specialist, CAIS

• 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
• 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

• 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
• Your expertise will 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

• Healthcare & wellness: We offer highly subsidized medical, dental, vision plan options, and monthly reimbursements to support your lifestyle outside of work
• Coverage Waiver Allowance: Have benefits through another source? Receive a monthly allowance for waiving coverage
• Voluntary benefits: Enjoy discounted pricing on virtual marketplace retail benefits, pet insurance, legal, identity theft, critical illness, hospital coverage, and additional life and AD&D insurance
• Paid parental leave: New parents receive up to 16 weeks of fully paid leave
• Flexible PTO: Take the time you need in coordination with your team and manager. Plus, enjoy nine paid holidays throughout the year
• 401(k) matching: Participate in a comprehensive 401(k) plan with a 4% match
• Free Food: Take advantage of our in-office lunch program and a fully stocked kitchen
• Team events: Join our monthly happy hours, team building activities, and other events to ensure we stay connected

Total funding: $395m

Financial advisors often face challenges in accessing education and alternative investment funds due to the absence of an integrated platform for discovering these opportunities. This gap can hinder their ability to offer clients diverse investment options and make informed decisions.