Senior Associate, Data Scientist - Audit Data Science
AI summary of the role
Senior Data Scientist on Audit Analytics and Innovation team building ML solutions for audit domains including LLM chatbots, GenAI apps, AML/fraud detection, and customer call intelligence.
What you’ll do
- Build and productionize ML/NLP models using Python, Hugging Face, LangChain
- Develop scalable data pipelines and validation frameworks
- Create visualization tools for model monitoring
- Partner with auditors, engineers, product managers to manage risk
What you’ll bring
- Bachelor's in quantitative field + 2 years data analytics or Master's/MBA quantitative
- Experience with Python/Scala/R (2+ years preferred)
- Machine learning experience (2+ years preferred)
- SQL experience (2+ years preferred)
Technologies
Python · Hugging Face · LangChain · AWS · Spark · H2O · Flask · Dash · Conda · NLP
Source and classification
Internal deployment & tooling · Evidence for this classification:
Innovation team. We’re not a traditional Data Science team: we build creative ML solutions across multiple domains, such as LLM based chatbots, GenAI powered applications, AML/Fraud identification, and Customer call transcripts intelligence. Opportunities to learn and build fast allow our team members to develop towards their full potential. We partner closely with product, tech, and design teams to enable faster build-to-market cycles for product features that delight our customers with dynamic and integrated experiences. You will be the driving force to experiment, innovate, and create next-generation features powered by the latest emerging NLP and Generative AI technologies. If you love a fast-paced, highly rewarding environment, and you love being a builder and communicator, this is the place for you. In this role, you will: Partner with a cross-functional team of data
More from the job description
Senior Associate, Data Scientist - Audit Data Science Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Innovation is at the heart of everything we do on the Audit Analytics and Innovation team. We’re not a traditional Data Science team: we build creative ML solutions across multiple domains, such as LLM based chatbots, GenAI powered applications, AML/Fraud identification, and Customer call transcripts intelligence. Opportunities to learn and build fast allow our team members to develop towards their full potential. We partner closely with product, tech, and design teams to enable faster build-to-market cycles for product features that delight our customers with dynamic [... source excerpt omitted ...] LP and Generative AI technologies. If you love a fast-paced, highly rewarding environment, and you love being a builder and communicator, this is the place for you. In this role, you will: Partner with a cross-functional team of data scientists, data analysts, risk professionals, software engineers, and product managers to manage risk and uncertainty in order to lead Capital One to the best decisions, not just avoid the worst ones Leverage a broad stack of technologies (Python, Conda, Flask, Dash, Hugging Face, LangChain, AWS, H2O, Spark, and more) to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning and NLP models through all p [... source excerpt omitted ...] You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathemati
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