Senior Director, Data Science, Applied Research

Team Description:

The AI Foundations team partners with product, tech, and business leaders to advance and deliver on our strategic vision to harness emerging AI advances, such as generative AI and continuous self-learning, while addressing fundamental invention challenges in AI for data (discovery, redaction, cleansing) and data for AI (fusing across sources, types, quality).

In this role, you will:

• Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.
• Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
• Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.
• Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The Ideal Candidate:

• Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
• Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
• Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
• Has a deep understanding of the foundations of AI methodologies.
• Experience building LLMs or large computer vision models as well as expertise in one or more key subdomain such as: training optimization, self-supervised learning, robustness, explainability, RLHF.
• An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
• Experience in delivered libraries, platform level code or solution level code to existing products.
• A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
• Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.

Basic Qualifications:

• Bachelor’s Degree plus 9 years of experience in data analytics, or Master’s Degree plus 7 years of experience in data analytics, or PhD plus 5 years of experience in data analytics
• At least 4 years of experience in applied AI Research
• At least 2 years of experience with Deep Learning
• At least 2 years of experience in applying research to production problems
• At least 2 years experience in developing and debugging in C/C++, Python, or C#

Preferred Qualifications:

• Master’s Degree or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
• At least 5 years of experience in AI Research
• Familiar with Financial services data sets
• At least 2 years experience with LLM practices such as prompt engineering, supervised fine tuning, distillation
• At least 4 years experience showing first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL)
• At least 5 years of experience in interdisciplinary research collaborations
• At least 4 years of experience in creating high-performance implementations of deep learning algorithms
• Successfully has mentored senior engineers across organizations

New York City (Hybrid On-Site):

$315,100 - $359,700 for Sr Dir, Data Science

San Francisco, California (Hybrid On-Site):

$333,900 - $381,000 for Sr Dir, Data Science

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.