Lead Quantitative Analytics Specialist

About this role:

Wells Fargo is seeking a Lead Quantitative Analytics Specialist. The AI Innovation & Modeling (AIM) organization is building scalable, production-grade AI capabilities that power advanced Predictive AI and Generative AI solutions. We are looking for a senior, hands-on engineer who can own end-to-end data ingestion and model-ready data pipelines (batch + streaming), accelerate cloud adoption on GCP, and help establish GenAI engineering and evaluation (LLMOps) practices to improve quality, reliability, and cost in production.

In this role, you’ll partner closely with data scientists, platform teams, and stakeholders to design and deliver robust ingestion frameworks, feature pipelines, and deployment-ready patterns — with a strong emphasis on performance, observability, and engineering excellence.

In this role, you will do:

• Data ingestion & pipeline engineering: Architect, build, and operate scalable ingestion pipelines across structured and unstructured sources (tabular, text, documents, audio, images) for batch and streaming use cases.
• Implement reliable transformation and storage patterns for analytics + modeling at scale (e.g., curated layers, reusable datasets, feature-ready tables).
• Establish strong data quality, validation, lineage, and auditability (data contracts, schema evolution, SLAs/SLOs).
• GCP-native delivery (preferred): Design and implement pipelines using GCP services such as BigQuery, GCS, Composer (Airflow), Dataflow, Pub/Sub, Dataproc, and related ecosystem tools.
• Support cloud migration of data/pipeline workloads from on‑prem to GCP, including environment onboarding, access patterns, and operational readiness.
• ML engineering: Build and standardize reusable components for feature engineering, feature stores, training/inference data pipelines, and deployment integration.
• Enable CI/CD for data and ML pipelines (testing, packaging, versioning, release strategy, rollbacks).
• GenAI engineering & evaluation (LLMOps): Implement evaluation harnesses for GenAI systems (offline + online), including dataset management, regression testing, metric dashboards, and experiment tracking.
• Apply evaluation techniques such as rubrics, LLM-as-judge, computation-based metrics and custom metrics to assess response quality, groundedness, safety, and instruction following. Integrate GenAI evaluation workflows using Vertex AI GenAI evaluation service and/or custom frameworks as appropriate.
• Performance & reliability: Lead performance optimization across pipeline runtime, cost, throughput, and scalability (partitioning, clustering, caching, parallelization, Spark tuning, query optimization).
• Build production-grade observability: monitoring, alerting, logging, tracing, and runbooks.
• Technical leadership: Provide senior technical leadership through design reviews, code reviews, best practices, and mentorship of junior engineers.
• Influence architecture and standards across teams; partner early in project scoping to recommend the right target-state pipeline patterns.

Required Qualifications:

• B.S/B.Tech/B.E. degree or higher in a quantitative field such as computer sciences, applied math, engineering
• Strong hands-on engineering experience building data ingestion and processing pipelines at scale (batch + streaming).
• Strong data sceince and ML engineering background preferred
• Advanced proficiency in Python and SQL, and at least one distributed processing framework (Spark preferred).
• Strong experience with GCP data and orchestration services (BigQuery, GCS, Composer/Airflow; Dataflow/PubSub a strong plus).
• Experience building production engineering practices: CI/CD, automated testing, monitoring/alerting, and operational support.
• Proven ability to collaborate with data science + platform teams and drive delivery across ambiguity.
• Ability to interact with both business and technology partners on tech migration/adoption

Desired Qualifications:

• Experience with Vertex AI Pipelines, feature stores, or ML workflow orchestration; familiarity with CI/CD + automation in ML systems.
• Experience with GenAI systems such as RAG ingestion pipelines, chunking/indexing strategies, prompt/tool orchestration, and evaluation/guardrails.
• Familiarity with AI/ML modeling frameworks and modeling techniques
• Experience in deploying Machine Learning as-a-service using REST API’s, Flask, Django, etc
• Experience with elastic search, knowledge graph good to have
• Experience working in regulated environments where data governance, access controls, and auditability matter.

Job Expectations:

• Good to have certifications in Data Science, Data Engineering, ML Ops, Cloud services
• Google Professional Cloud architect, Google AI/ML Certification
• Keywords: GCP, BigQuery, GCS, Cloud Composer, Dataflow, Pub/Sub, Dataproc, Spark, Python, SQL, Vertex AI, Feature Store, ML pipelines, CI/CD, Kubernetes/GKE, Docker, LLMOps, GenAI evaluation, RAG ingestion, observability, performance tuning.

Posting End Date: 

7 Apr 2026

*Job posting may come down early due to volume of applicants.

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.

Drug and Alcohol Policy

 

Wells Fargo maintains a drug free workplace.  Please see our Drug and Alcohol Policy to learn more.

Wells Fargo Recruitment and Hiring Requirements:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.