Principal Associate, Data Scientist - Tech Innovation Hub

Principal Associate, Data Scientist – People Tech Innovation Hub

Apply for the Principal Associate, Data Scientist – People Tech Innovation Hub role at Capital One
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Data is at the center of everything we do. As a startup, we disrupted the credit card industry by personalizing every credit card offer using statistical modeling and relational databases, building a treasure trove of data and technology. Today, Company One is a Fortune 200 leader in data‑driven decision‑making.

As a Data Scientist, you will be part of a team that is leading the next wave of disruption at a whole new scale, using the latest computing and machine learning technologies to unlock opportunities across billions of customer records and help people save money, time, and financial stress.

Capital One’s People Technology Innovation Lab is hiring a Data Scientist to translate raw data into game‑changing insights and products. You’ll tackle complex, high‑impact challenges with Generative AI, Knowledge Graphs, and other cutting‑edge technologies to shape the employee experience and drive our culture of innovation.

In this role, you will:

• Partner with a cross‑functional team of data scientists, software engineers, and product managers to deliver a product customers love.
• Leverage a broad stack of technologies—including Python, Conda, AWS, H2O, Spark, and more—to reveal insights hidden in large volumes of numeric and textual data.
• Build machine learning models across all development phases, from design and training to evaluation, validation, and implementation.
• Translate complex data science work into clear, tangible business goals.

• Innovative: Continuously research emerging technologies and find opportunities to apply state‑of‑the‑art methods.
• Creative: Thrive on def‑ining large, ambiguous problems and pioneering solutions.
• Statistically‑mind बैंक: Experienced with model building, validation, backtesting, and interpreting performance metrics such as confusion matrices, ROC curves, clustering, classification, sentiment analysis, time‑series analysis, and deep learning.
• Data guru: Comfortable with “big data,” retrieving, combining, and analyzing diverse data sources to drive insight.

• Currently has or is obtaining a degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) with the required level of experience:
  • Bachelor’s: 5 years of data analytics experience.
  • Master’s / MBA: 3 years of data analytics experience.
  • PhD: 0 years of data analytics experience.

• Master’s or PhD in a STEM field with 3+ years of data analytics experience.
• At least 1 year of AWS experience.
• At least 3 years of Python/Scala experience.
• At least 3 years of machine learning experience.
• At least 3 years of SQL experience.
• At least 1 year of']; }