Associate AI | ML Engineer

• Design develop and optimize prompts for Large Language Models (LLMs).
• Collaborate with data scientists and play a role in defining testing and optimizing prompts that guide our AI systems to generate accurate informative and creative outputs.
• Create and improve AI models and algorithms as well as maintain prompt libraries to generate prompts for natural language processing (NLP) applications.
• Stay abreast of most recent developments on large language models.

• University (Degree) Preferred

• 3 Years Required; 5 Years Preferred

• Physical Requirements: Sedentary Work

About the Role
We are looking for a curious analytically rigorous and collaborative Data Scientist to join our growing this role you will work closely with business stakeholders data engineers and product teams to transform raw data into actionable insights and production-ready machine learning solutions. You will own the full modeling lifecycle from problem framing and data exploration through model development validation and deployment with a primary focus on supervised learning applications including regression and classification.

This is an excellent opportunity for someone who has moved beyond foundational data science work and is ready to take on greater ownership of projects while continuing to grow their technical depth and business acumen.

Key Responsibilities
Modeling & Machine Learning You will develop validate and maintain supervised machine learning models including linear and logistic regression decision trees random forests gradient boosting methods (XGBoost LightGBM) and support vector machines. You will apply sound practices around feature engineering hyperparameter tuning cross-validation and model selection to ensure robust generalizable solutions.

Data Preparation & Exploration You will partner with data engineering teams to source clean and transform structured and semi-structured datasets. You will conduct thorough exploratory data analysis to surface patterns anomalies and opportunities that inform both modeling strategy and business decisions.

Model Evaluation & Interpretation You will apply appropriate evaluation metrics such as RMSE MAE AUC-ROC precision-recall F1 R² and lift curves to assess model performance in context. You will leverage model explainability techniques (e.g. SHAP values partial dependence plots) to communicate findings clearly to both technical and non-technical audiences.

Deployment & Monitoring You will collaborate with engineering and MLOps teams to package and deploy models into production environments. You will establish monitoring frameworks to track model drift data quality issues and performance degradation over time and will lead remediation efforts when needed.

Stakeholder Engagement You will translate complex analytical findings into clear compelling narratives for business stakeholders. You will contribute to project scoping discussions help define success metrics and proactively surface risks or limitations in proposed analytical approaches.

Mentorship & Knowledge Sharing You will contribute to the teams collective growth by participating in code reviews documenting your work thoroughly and sharing learnings through internal presentations or knowledge repositories.

Required Qualifications
3 to 5 years of hands-on experience in data science or a closely related quantitative role
Strong proficiency in Python including libraries such as scikit-learn pandas NumPy and matplotlib. Experience in Domino Lab is a plus.
Demonstrated experience building and deploying regression and classification models in a business context
Solid understanding of statistical fundamentals including probability hypothesis testing and model assumptions
Experience working with SQL for data extraction and transformation
Familiarity with version control using Git and collaborative development practices
Strong written and verbal communication skills with the ability to present technical work to diverse audiences
Preferred Qualifications
Experience with cloud platforms such as AWS Azure or GCP and their respective ML services
Familiarity with MLflow Kubeflow or similar experiment tracking and model registry tools
Exposure to imbalanced classification problems and techniques such as SMOTE or cost-sensitive learning
Experience with time series regression or survival analysis
Background in financial services insurance healthcare or other regulated industries
Bachelors or advanced degree in Statistics Mathematics Computer Science Data Science or a related quantitative field

Company Overview

TIAA Global Capabilities was established in 2016 with a mission to tap into a vast pool of talent reduce risk by insourcing key platforms and processes as well as contribute to innovation with a focus on enhancing our technology stack. TIAA Global Capabilities is focused on building a scalable and sustainable organization with a focus on technology operations and expanding into the shared services business space.

Working closely with our U.S. colleagues and other partners our goal is to reduce risk improve the efficiency of our technology and processes and develop innovative ideas to increase throughput and productivity.

We are an Equal Opportunity Employer. TIAA does not discriminate against any candidate or employee on the basis of age race color national origin sex religion veteran status disability sexual orientation gender identity or any other legally protected status.

Our Culture of Impact

At TIAA were on a mission to build on our 100 year legacy of delivering for our clients while evolving to meet tomorrows challenges. We equip our associates with future-focused skills and AI tools that enable us to advance our mission. Together we are fighting to ensure a more secure financial future for all and for generations to come. We are guided by our values: Champion Our People Be Client Obsessed Lead with Integrity Own It and Win As One. They influence every decision we make and how we work together to serve our clients every day. We thrive in a collaborative in-office environment where teams work across organizational boundaries with shared purpose accelerating innovation and delivering meaningful results. Our workplace brings together TIAA and Nuveens entrepreneurial spirit where we work hard and work together to create lasting impact. Here every associate can grow through meaningful learning experiences and development pathwaysbecause when our people succeed our impact on clients lives grows stronger.

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