Principal Data Science Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Wells Fargo is seeking a Principle Engineer in technology as part of Commercial and Corporate & Investment Banking Technology (CCIBT) within the Investment Portfolio (IP) technology team to lead all data science activities while leveraging our data science tools and technologies to meet business objectives, create a data science platform strategy and advance our Artificial Intelligence (AI) and Machine Leaning (ML) initiatives. This senior engineer will mentor a large community of data analysts and scientists and provide technical leadership to and partnership with technology teams to build out data science pipelines to support continuous testing, optimization, and implementation of new models.

In this role, you will:

• Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups
• Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking
• Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions
• Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions
• Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization
• Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership

Required Qualifications:

• 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 7+ years of python experience
• 5+ years of experience with Jupyter/JupyterHub
• 5+ years of experience working within a data science environment
• 3+ years of experience with Artificial Intelligence (AI) and Machine Learning (ML)

Desired Qualifications:

• Experience with one or a combination of the following cloud platform applications: Google Cloud Platform (GCP), Azure
• Experience building cloud native applications
• Experience with version control, source code repositories and CI/CD pipelines to include: Git/ Github, Jenkins
• Experience with data science tools to include: Python, Jupyter, JupyterHub, Airflow, MLFlow, Sphinx, pandas, sqlalchemy , tensorflow, pytest
• Experience with governance and control processes within a large financial institution

Locations:

• 150 E 42nd St., New York, NY 10017
• 333 Market St., San Francisco, CA 94105
• 301 S Tryon St., Charlotte, NC 28282

Pay Range

$144,400.00 - $300,000.00 Annual