iCapital is powering the world’s alternative investment marketplace. Our financial technology platform has transformed how advisors, wealth management firms, asset managers, and banks evaluate and recommend bespoke public and private market strategies for their high-net-worth clients. iCapital services approximately $200 billion in global client assets invested in 1,634 funds, as of September 2024.
iCapital has been named to the Forbes Fintech 50 for seven consecutive years (2018-2024); a three-time selection by Forbes to its list of Best Startup Employers (2021-2023); and a four-time winner of MMI/Barron’s Solutions Provider award (See link below).
About the Role
iCapital's AI/ML team is developing cutting edge solutions to establish a unique competitive edge for the company. The Data Scientist role will play a key role in developing AI models and engineering iCapital’s core machine learning and AI products. This individual will be working in a collaborative team environment across machine learning, product management, data engineering, and software engineering teams. The ideal candidate will be passionate about leveraging machine learning techniques to drive innovation and have a strong background in researching and developing AI models.
Responsibilities
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Build and integrate AI/ML/DS tools and workflows to address business needs and increase business efficiency.
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Support the design, development, training, and deployment of AI/ML models and engineering solutions to solve business problems through a full development and production cycle in the FinTech domain.
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Build and leverage new and existing tools for Large Language Model (LLM), Natural Language Processing (NLP), Optical Character Recognition (OCR), and intelligent document processing tasks.
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Evaluate and compare the performance of different AI/ML algorithms and models.
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Contribute to the improvement of Machine Learning Operations (MLOps) pipelines and procedures to ensure efficiency, scalability, and maintainability.
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Ensure the reliability, robustness, and scalability of machine learning models in production environments.
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Collaborate with cross-functional teams, including machine learning engineers, product managers and full stack engineers, to deliver scalable machine learning solutions.
Qualifications
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4-8 years of experience as a hands-on data scientist or AI/ML engineer in AI/ML/DS fields
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Advanced degree in a relevant field such as AI, ML, Data Science, mathematics, or computer science.
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Experience building ML and AI models and systems in a production environment in at least Generative AI/LLM or NLP applications
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Experience working with LLM, such as GPT-4, Llama 3, Mistral, and other commercial or open-source models in a production environment
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Knowledge of NLP techniques, including text data preprocessing (tokenization, stemming, and text normalization, etc.) and information extraction (summarization, and question answering, etc.)
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Proficiency in programming languages in Python, and libraries/frameworks like TensorFlow, PyTorch, spaCy and scikit-learn, etc
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Strong knowledge of machine learning algorithms and statistical techniques, their limitations, and implementation challenges
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Experience with cloud platforms and distributed computing environments, such as AWS, Google Cloud, or Azure
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Experience working in a finance or financial technology job with alternative investments
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Direct contributions to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results
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Strong problem-solving skills and able to work independently and collaboratively in a fast-paced, agile environment
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Strong communication skills and able to effectively articulate technical concepts to both technical and non-technical audiences
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Experience with data visualization tools and techniques to effectively communicate and present findings
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Publication record as a lead author or essential contributor at top venues such as CHI, NeurIPS, UIST, ICML, ICLR, ACL, EMNLP, CVPR, AAAI, and/or ICAPS
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Portfolio of personal projects on Github, BitBucket, Google Colab, Kaggle, etc.
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Understanding of regulatory and compliance requirements in the financial industry and their implications for machine learning applications
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Experience with software development best practices, including source control (Git), CI/CD pipelines, testing, and documentation
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Familiar with database integration principles and practices, including SQL and NoSQL databases and data warehouse solutions, such as Snowflake
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Experience with data transformation tools, such as dbt, and orchestration tools such as Airflow
Benefits
The base salary range for this role is $130,000 to $160,000. iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).
We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.
For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/
iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
