Senior Associate, Data Scientist - People Strategy & Analytics
$135.6k - $154.8kCapital One Financial Corp
Senior Associate, Data Scientist - People Strategy & Analytics
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. Team Description People Strategy & Analytics brings data, analytics, and insights to shape critical talent decisions and strategy at Capital One. We work closely with HR partners and senior executives in shaping talent policy, automating real-time data, and improving talent decision-making. The team is comprised of people with diverse skills and backgrounds including: data analysts, data scientists, business analysts, HR specialists, project managers, and industrial/organizational psychologists. As a Data Scientist on Capital One's People Strategy & Analytics team, you'll be on the leading edge of applying analytics to talent, combining artificial intelligence, machine learning, and social science to build models that seek to understand associate behavior, improve HR efficiency and tools, and inform strategies aimed at expanding Capital One's talent advantage. Role Description In this role, you will:- Support development of natural language processing and machine learning models through all phases, from design through training, evaluation, validation, and implementation
- Apply expertise in using open source large language models (LLMs) through prompt engineering, retrieval-augmented generation (RAG) and evaluation metric frameworks for business specific applications
- Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading HR tools and AI-powered products
- Leverage a broad stack of technologies - Python, SQL, AWS, LangChain, Hugging Face Transformers, VectorDBs, Pytorch/TensorFlow, and more - to reveal the insights hidden within large volumes of numeric and textual data
- Flex your interpersonal skills to collaborate with internal stakeholders, translating complex data science work into tangible, aligned business outcomes.
- Passionate about human capital: You are excited by the value we can add to our company and our associates, and are inspired to help make a large positive impact.
- Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
- Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.
- Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
- Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
- 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, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration
- Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics), or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)
- Experience working with AWS
- At least 2 years' experience in Python
- At least 2 years' experience with machine learning
- At least 2 years' experience with SQL
- At least 1 year experience with relational databases such as Snowflake
- At least 1 year experience with AI/ML tools and ecosystems such as Hugging Face, VectorDBs or Pytorch/TensorFlow
Vacancy posted 1 day ago
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