Data Science Manager

Rahul Singh

GenAI Leader — AI Strategy — Machine Learning Ops

518-***-****

# *********@*****.***

ð linkedin.com/in/rahulsn

Experience

Leadership Experience

2023–Present Quantitative Analytics Manager – GenAI & NLP, Wells Fargo

Lead and mentor a high-performing team of 8 applied scientists and engineers, overseeing technical strategy, hiring, performance, and career development.

Spearheading cross-functional collaboration across Engineering, and Data Science to deliver impactful AI solutions projected to impact 1000+ users.

Developed a 7-part GenAI training series, educating 500+ stakeholders and accelerating AI adoption across departments.

Led prioritization of use cases and resource planning to ensure optimal delivery of high-impact ML initiatives.

Established and governed enterprise-grade NLP/LLM libraries with best practices in testing, versioning, and CI/CD pipelines using Jenkins, GitHub Actions.

Oversaw the deployment of secure, large-scale LLM applications, ensuring compliance with data privacy and model monitoring standards.

Promoted a culture of experimentation and data-informed decision making through robust A/B testing and validation protocols.

Directed the design and development of scalable pipelines—including data, model, and testing pipelines—to support end-to-end ML lifecycle management.

Spearheaded research in model fairness, bias mitigation, and ethical AI development

Implemented AI governance framework with guardrails for risk management, fairness, and ethical considerations.

Technical and Applied Experience

2019–2023 Lead/Senior Quantitative Analytics Specialist, Wells Fargo

Designed, built, and maintained modular AI libraries powering scalable NLP and ML applica- tions.

Developed automated MLOps workflows, including training, evaluation, deployment, and monitoring pipelines.

Partnered with cross-functional teams to transform ambiguous business problems into struc- tured data science solutions.

Conducted foundational research in adversarial robustness, interpretability, and efficiency of deep learning models.

Built custom LLM training pipelines using PyTorch and investigated DeepSpeed for distributed multi-GPU training

Developed custom evaluation frameworks and domain-specific benchmarks for financial NLP tasks

Created data processing pipelines for LLM training with robust cleaning, deduplication, and filtering mechanisms

Explored model compression techniques including novel attention head pruning approaches

Led research in paraphrase evaluation metrics and deep ReLU network interpretability Education

2013–2018 Ph.D., Mechanical Engineering, Iowa State University 2017–2018 Master’s in Computer Science, Iowa State University 2007–2012 B.Tech-M.Tech, Mechanical Engineering, IIT Kanpur Technical Expertise

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GenAI/NLP LLMs (GPT, T5, LLaMA), Prompt Engineering, RAG, Fine-tuning, Domain-Specific Models, Model Evaluation

Machine Learning Supervised/Unsupervised Learning, Transfer Learning, Deep Learning, Interpretability, Model Compression

MLOps CI/CD, Jenkins, Model Monitoring, MLFlow

Data Stack SQL, Python, Spark, Tableau

Programming Python, PyTorch, TensorFlow, C++, SQL, Java, Shell Scripting Patents & Publications

Patents

2024 Singh R, Jindal K, Yu Y, Yang H, Joshi T, Campbell M A, Shoumaker W B; Ad- versarial input generation for natural language processing machine learning models, US20240273293A1

2023 Joshi T, Singh R, Nair V, Sudjianto A; Systems and methods for natural language processing (NLP) model robustness determination, US12073181B2 Selected Publications

2024 Li Y, Singh R, Joshi T, Sudjianto A; Automatic Generation of Behavioral Test Cases For NLP Using Clustering and Prompting, arxiv

2022 Patil O, Singh R, Joshi T; Understanding Metrics for Paraphrasing, arxiv 2022 Raste S, Singh R, Vaughan J, Nair Vijayan N; Quantifying Inherent Randomness in ML Algorithms, SSRN

2021 Singh R, Joshi T, Nair Vijayan N; Robustness Tests of NLP ML Models: Semantic- preserving adversarial attacks, arxiv

2021 Parnami A, Singh R, Joshi T; Pruning Attention Heads of Transformer Models Using A* Search, arxiv

2020 Sudjianto A, Knauth W, Singh R, Yang Z, Zhang A; Unwrapping The Black Box of Deep ReLU Networks, arxiv

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