Associate

Associate - Data Scientist - IN
The Data Scientist participates in the effort to obtain business insights from large data sets through complex data research and analysis. Under general supervision, this role contributes to development of data mining and data analysis methodologies to create algorithms and predictive models. This job is responsible for analyzing the current data mining and data analysis methodologies to implement new processes as needed.

Key Responsibilities and Duties

• Develops and implements data mining protocols, architectures, and models as well as data analysis methodologies, used to identify trends in large data sets.
• Cooperates in developing new data mining and data analysis processes as needed to improve effectiveness and accuracy of data analyses, based on research of existing and emerging data science principles, theories and techniques.
• Prepares statistical reporting, data analyses insights, and data visualizations, used to better understand client relationships and improve client services and product offerings.
• Consulting on using business intelligence data for predictive analytics and facilitating implementation of new tools.
• Inspects the acquisition of data from structured and unstructured sources, while ensuring quality and comprehensiveness of the data.
• Coordinates research and analytic activities utilizing various data points and employ programming to clean and organize data.

Educational Requirements

• University (Degree) Preferred

Work Experience

• 2+ Years Required; 3+ Years Preferred

Physical Requirements

• Physical Requirements: Sedentary Work

Career Level
6IC

Position Summary:  Describe below the primary purpose and function of this job

We are seeking a skilled Generative AI Engineer with expertise in prompt engineering to design, build, and optimize AI-powered solutions leveraging state-of-the-art generative models such as GPT, LLama, Claude, Gemini and others. This role focuses on crafting effective prompts, fine-tuning models - potentially be involved in fine-tuning efforts, and integrating generative AI capabilities into applications to solve business challenges and enhance user experiences.  

As a Generative AI Engineer, you will work closely with cross-functional teams to understand requirements, design AI-driven workflows, and deliver innovative solutions that maximize the potential of generative AI.  

 

Key Duties & Responsibilities:  List up to 5 key duties and responsibilities, management responsibilities and time spent (if applicable)

1. Prompt Engineering and Optimization:  
  - Craft, test, and refine effective prompts to achieve desired outputs from generative models.  
  - Develop reusable prompt templates for various tasks such as content generation, summarization, translation, or creative design.  
  - Experiment with prompt tuning and parameter adjustments for optimal performance.  

2. Generative AI Solution Development:  
  - Integrate large language models (LLMs) and generative AI tools into applications and workflows.  
  - Develop APIs or interfaces for user-friendly access to generative AI capabilities.  
  - Fine-tune pretrained generative models to align with specific domain requirements.  

3. Data Preparation, Model Fine-tuning and Optimization:  
  - Prepare and preprocess datasets for model training or fine-tuning.  

  - Potentially be involved in fine-tuning efforts.
  - Evaluate and improve models for specific tasks, ensuring reliability and accuracy.  

4. Performance Evaluation and Quality Assurance:  
  - Monitor and evaluate the performance of generative models using metrics like perplexity, BLEU, ROUGE, or custom KPIs.  
  - Address biases, fairness, inaccuracies, or hallucinations in generated outputs.  

5. Collaboration and Documentation:  
  - Work closely with stakeholders to identify use cases and translate requirements into generative AI solutions.  
  - Document best practices, workflows, and insights gained during prompt engineering and model optimization.  

6. Innovation and Research:  
  - Stay updated with the latest advancements in generative AI, prompt engineering, and related fields.  
  - Experiment with emerging models and techniques to push the boundaries of generative AI applications

 

Management/Leadership Responsibility:  Is management of people a primary focus of the role?  If so, how many direct and indirect employees are managed?  Do any of them manage a function or process?

NA

Budget Responsibility: Does the position have responsibility for Revenue, Operating (expense) Budget, etc.?  If so, what is the scope?

N/A

Impact:

NA

NA

Business or Industry Expertise:  Describe the degree of knowledge and understanding required of TIAA’s business and industry, commercial environment and of competitors products and services.

Interactions / Interpersonal Skills:  Describe the nature and level of interactions this job has with others, both internally and externally.  Explain any specific interpersonal skills necessary to successfully perform this role (i.e., negotiation skills, represents business at external events or to governmental bodies, etc. ).

Job Requirements And Qualifications:  Indicate the minimum and preferred education and experience for the job and any licenses and certifications required

Required Education:

BA/BS

(add “other” details here)

Preferred Education:

Masters

(add “other” details here)

Skills and Abilities:

Generative AI Expertise: 

- Hands-on experience with generative AI models like GPT (e.g., GPT-4), LLama, Claude, Gemini, or similar.  
- Proficiency in crafting, testing, and refining prompts for LLMs to handle diverse tasks effectively.  
- Experience with prompt engineering techniques, including prompt-tuning, instruction-based learning, and chain-of-thought prompting.  
- Experience with Retrieval-Augmented Generation (RAG) techniques, integrating external knowledge bases with LLMs for enhanced context and accuracy.

Programming Skills:
- Proficiency in Python, including libraries like Transformers (Hugging Face), OpenAI API, LangChain, PyTorch, TensorFlow.  
- Experience with integrating AI models into applications through APIs or SDKs.  

Model Optimization, Fine-tuning & Deployment:
- Knowledge of transfer learning and fine-tuning methods for pretrained models.  
- Experience deploying AI models on cloud platforms (e.g., AWS Sagemaker, Azure AI, Google Vertex AI).  
- Familiarity with containerization tools like Docker and orchestration systems like Kubernetes.  

Data Preparation and Analysis:
- Proficiency in data preprocessing, annotation, and augmentation techniques.  
- Understanding of embeddings and vectorization for tasks like semantic search or similarity scoring.  

Collaboration and Communication:
- Ability to work with non-technical stakeholders to design user-centric AI solutions.  
- Strong communication skills to explain complex AI outputs and design choices clearly.  

Preferred Qualifications:
- Familiarity with reinforcement learning from human feedback (RLHF).  
- Knowledge of ethical AI principles and techniques to mitigate biases in generative models.  
- Experience with frameworks like LangChain for building AI agents or pipelines.  
- Exposure to visualization tools for generative outputs (e.g., streamlit, Gradio).  

Related Skills

Business Acumen, Data Preprocessing, Data Science, Innovation, Machine Learning, Market/Industry Dynamics, Predictive Modeling, Programming, Statistics

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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/Affirmative Action Employer. We consider all qualified applicants for employment regardless of age, race, color, national origin, sex, religion, veteran status, disability, sexual orientation, gender identity, or any other protected status.

Accessibility Support

TIAA offers support for those who need assistance with our online application process to provide an equal employment opportunity to all job seekers, including individuals with disabilities.

If you are a U.S. applicant and desire a reasonable accommodation to complete a job application please use one of the below options to contact our accessibility support team: 

Phone: (800) 842-2755

Email: accessibility.support@tiaa.org

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