Applied AI ML - Sr. Associate

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Category:
Predictive Science

Job Schedule:

Full time

Posted Date: T19:54:19+00:00

Job Shift:

Base Pay/Salary:
New York,NY $-$

We're building the AI‑native, data‑driven future of HR at a leading global financial institution. With 300,000+ employees across 60+ countries, our AI team in HR Data and Analytics develops research and production solutions that help leaders make smarter, evidence‑based decisions-shaping how our global workforce operates.

As a Vice President - Applied AI/ML in HR Data and Analytics, you apply quantitative, data science, and analytical skills to complex workforce challenges. You partner with domain experts and cross‑functional teams to design, develop, and scale AI/ML solutions from foundational research through production deployment. Your work drives strategic initiatives that shape the firm's business and the employee experience at scale, with opportunities for personal and professional growth on a world‑class data science team.

Job responsibilities

* Engage with stakeholders to identify and define business needs and opportunities, and design technical solutions to address them.

* Partner with product managers, engineers, and functional experts across the end‑to‑end AI/ML lifecycle-conception, validation, scaling, production delivery, and performance monitoring.

* Perform AI model evaluations and monitoring; develop structured verification systems to ensure accuracy, safety, and reliability.

* Conduct research that advances the technical foundations of AI and data science capabilities.

* Collaborate with teams across the firm to advance mission and vision.

Required qualifications, capabilities, and skills

* Advanced degree (master's or higher) in Computer Science, Data Science, Engineering, Applied Mathematics, Statistics, or a related quantitative discipline.

* 2+ years of experience developing and deploying AI/ML solutions with hands‑on coding and end‑to‑end solution design.

* Strong programming skills in Python; including experience with libraries such as Tensor Flow, PyTorch, Keras, or scikit‑learn.

* Demonstrated expertise in machine learning techniques (supervised, unsupervised, semi‑supervised), natural language processing (NLP), generative AI, or computer vision.

* Practical experience with Large Language Models (LLMs), including fine‑tuning, prompt and context engineering, and RAG pipelines.

* Understanding of agentic AI systems and their design principles.

* Demonstrate strong analytical and problem‑solving skills; thrive in cross‑functional, collaborative team environments.

Preferred qualifications, capabilities, and skills

* Hold a PhD in a relevant discipline.

* Experience in the financial services industry.