Senior Data Science Consultant - Enterprise Complaints, Remediations & Loudspeaker
Wells Fargo•1d ago
United StatesRemoteFull-timeSenior Level4+ yrs exp
H-1B verified · 111 LCAs
Top focus
Data ConsultantVp DataSenior Data AnalystSenior Data ScientistData Scientist
- Why Wells Fargo Are you looking for more? Find it here. At Wells Fargo, we're more than a financial services leader – we’re a global trailblazer committed to driving innovation, empowering communities
- helping our customers succeed. We believe that a meaningful career is much more than just a job – it’s about finding all of the elements to help you thrive, in one place. Living the Well Life means you’re supported in life, not just work. It means having robust benefits, competitive compensation
- programs designed to help you find work-life balance and well-being. You’ll be rewarded for investing in your community, celebrated for being your authentic self
- empowered to grow. Join us! About this role Wells Fargo Enterprise Complaints, Remediations and Loudspeaker Analytics (ERA) is seeking a Senior Data Science Consultant focused on advanced analytics and AI solutions supporting voice‑of‑customer insights, risk identification
- operational decisioning . This role is strongly oriented toward applied Generative AI , with a primary focus on designing, experimenting with
- evaluating LLM‑enabled systems that operate on large volumes of unstructured customer interaction data. The consultant will own the end‑to‑end experimentation lifecycle for GenAI use cases — including prompt and agent design, iterative testing, error analysis, tuning
- evaluation — while leveraging traditional machine learning and NLP techniques where appropriate to support or augment GenAI solutions. The role emphasizes practical execution, rapid prototyping
- disciplined evaluation to ensure outputs are reliable, explainable
- suitable for use in risk‑aware, human‑in‑the‑loop decision environments. In this role, you will Lead hands‑on Generative AI experimentation , including prompt engineering, prompt library development
- agent‑style workflows that support voice‑of‑customer understanding, issue identification
- decision support. Design and execute systematic testing of LLM outputs across large collections of historical customer interaction data, evaluating behavior across tasks, data conditions
- edge cases. Conduct deep error analysis of GenAI outputs , identifying hallucinations, weak or missing evidence, false positives, false negatives
- translate findings into targeted prompt and system improvements. Develop and apply GenAI evaluation frameworks , including rule‑based heuristics, statistical indicators
- LLM‑as‑a‑Judge techniques, to assess output quality, consistency
- risk. Build and refine confidence and uncertainty scoring mechanisms for LLM decisions to support prioritization and secondary human review in higher‑risk scenarios. Apply machine learning and NLP models where appropriate to complement GenAI solutions, such as feature extraction, classification, clustering
- signal generation. Analyze complex structured and unstructured datasets to generate hypotheses, surface emerging risks
- identify opportunities where GenAI can augment or automate decision workflows. Collaborate closely with product teams, engineers
- business stakeholders to align GenAI experimentation with operational workflows, risk tolerance
- real‑world constraints. Produce clear documentation of prompts, experiments, evaluation methods
- findings to ensure transparency, repeatability
- knowledge sharing. Communicate GenAI behaviors, trade‑offs, limitations
- risks effectively to non‑technical stakeholders, helping set appropriate expectations for usage. May mentor teammates by sharing best practices related to GenAI experimentation, evaluation
- responsible deployment. Required Qualifications
- 4+ years of data science experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science Desired Qualifications Strong hands‑on experience with Python‑based experimentation and analytics workflows , working with large structured and unstructured text datasets
- SQL proficiency required, SAS/Teradata a plus. Demonstrated practical experience building and testing Generative AI solutions , including prompt engineering, prompt tuning, task decomposition, and agent‑style workflows using LLMs . Proven ability to perform LLM evaluation and error analysis , including hallucination detection, output quality assessment, and false positive/false negative analysis. Experience designing or implementing confidence, uncertainty, or risk‑scoring mechanisms for GenAI outputs to support review and escalation decisions. Familiarity with Machine Learning and NLP modeling techniques, and the ability to apply them selectively to complement GenAI‑driven approaches. Ability to design repeatable testing methodologies, benchmarks, and success metrics for GenAI systems operating in risk‑sensitive environments. Strong communication skills, with the ability to clearly explain GenAI behaviors, limitations, and experimental findings to both technical and non‑technical audiences. Experience producing high‑quality documentation covering prompts, experiments, evaluation methods, and system behaviors. Comfortable operating in ambiguous problem spaces, with an execution mindset focused on experimentation, learning, and continuous improvement. Strong statistical background and deep understanding of statistical methods for extracting insight from large, complex datasets. Hypothesis driven, investigative or “detective like” approach to identifying anomalies, edge cases, unexpected behaviors, and weak signals in both data and model outputs. Comfort applying statistical reasoning to error analysis, uncertainty estimation, and validation of GenAI and ML driven results. Job Expectations:
- Ability to travel up to 10% of the time.
- This position is NOT eligible for Visa sponsorship.
- Ability to work on site per Wells Fargo's standard operating model in one of the listed locations. Posting Locations:
- CHANDLER, AZ
- SAN ANTONIO, TX
- WEST DES MOINES, IA
- MINNEAPOLIS, MN
- CHARLOTTE, NC
- IRVING, TX The Chief Operating Office Functions adhere to a location strategy
- therefore, your candidacy may be determined based on your current location. Remote work locations are not available for these roles, so if you are not in a location listed on the posting, you must commit to self-relocation within an agreed upon timeframe. Pay Range Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities. $119,000.00 - $206,000.00 Benefits Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees. Health benefits 401(k) Plan Paid time off Disability benefits Life insurance, critical illness insurance, and accident insurance Parental leave Critical caregiving leave Discounts and savings Commuter benefits Tuition reimbursement Scholarships for dependent children Adoption reimbursement Posting End Date: 19 Jun 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. 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.
Required skills
PythonSQLSASTeradataMachine LearningNLPGenerative AI