New York City (Hybrid On-Site): $201,400 - $229,900 for Mgr, Data Science
San Francisco, California (Hybrid On-Site): $213,400 - $243,500 for Mgr, Data Science
Our client is looking for an experienced Manager, Data Science - NLP to lead a team of talented data scientists and engineers. In this role, you will develop and implement cutting-edge NLP models and solutions to enhance customer experience, streamline operations, and support strategic decision-making.
Key Responsibilities:
- Lead a team of data scientists and NLP specialists in designing, developing, and deploying NLP models and solutions across multiple domains.
- Collaborate with cross-functional teams, including product managers, software engineers, and business analysts, to integrate NLP models into Capital One’s products and services.
- Identify, evaluate, and implement new data sources and technologies to enhance model performance and deliver actionable insights.
- Develop and maintain a strong understanding of emerging NLP trends, tools, and techniques, and apply them to solve business problems.
- Ensure the scalability, robustness, and compliance of NLP models in production environments.
- Provide mentorship, coaching, and career development support to team members.
- Drive data science best practices, including model governance, experimentation, and reproducibility.
Qualifications:
- Currently has, or is in the process of obtaining a Bachelor’s Degree plus 6 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 4 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date
- At least 2 years of experience in open source programming languages for large scale data analysis
- At least 2 years of experience with machine learning
- At least 2 years of experience with relational database
- Experience with cloud computing platforms (e.g., AWS, GCP, Azure).
- Excellent communication and collaboration skills, with the ability to translate complex technical concepts to non-technical stakeholders.
- Strong problem-solving skills and the ability to think strategically.