Senior Data Scientist

2 weeks ago

Omaha, United States Charles Schwab Full time
Your Opportunity

At Schwab, you're empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us "challenge the status quo" and transform the finance industry together.

The Schwab Capacity Planning Team, within the Application Architecture team is looking for a seasoned, driven, and curious senior data scientist passionate about ensuring capacity and availability of critical applications and systems to meet client demands. The candidate will be relied upon for their expertise to handle large volumes of data and raw information, and apply model strategies to predict and extract valuable business insights. Working across business and technology domains, this role will help to drive application capacity strategy and direction across a wide variety of activities, such as public cloud adoption, acquisitions and integrations, application modernization, and digital enablement. The role requires close collaboration with architects and engineers across the Schwab Technology Services (STS) organization.

This role reports up to the Office of the CTO (Chief Technology Office), chartered to establish technology governance, standards, practices, and strategy for the entire firm, enabling thousands of technologists to better serve the millions of Schwab clients and trillions of dollars in client assets.

Specific goals will include:
  • Create modeling capabilities to help predict capacity issues based on past trends, client expectations, and new environments.
  • Assess current capacity baseline for the most critical business functions.
  • Translate the impact of capacity issues into business performance measures.
What you have

Required Qualifications
  • B.S. / B.A in Computer Science, Engineering, Data Science or in Statistical and other quantitative field is minimally required.
  • 7+ years of experience in an analytical role consulting with internal business partners and a consistent track record of performing data analysis in highly regulated industries (e.g., finance, insurance, health care, government)
  • 5+ years of experience as a Data Scientist with data mining experience.
  • 4+ years of experience in using the SQL and Python data science stack (Pandas, NumPy, Matplotlib, Scikit-Learn, Jupyter, etc.) or equivalent.
  • 3+ years of experience in machine learning, operations research and developing descriptive, predictive, and prescriptive data modeling techniques.
  • 5+ years of experience using business intelligence, analytics, and visualization tools (e.g., Tableau) and data frameworks.
  • 3+ years of experience working in design analysis and problem-solving, in close collaboration with subject matter experts from varying technology and business disciplines.
  • 3+ years of experience working effectively at all levels of an organization with the ability to influence others, inspire others and to lead decisions that provide clear positive results to the company.
Preferred Qualifications
  • Master's or advanced degree.
  • Experience in financial, investment management and securities markets.
  • Strong technical background and experience in application hosting or application development, architecture, and design, with positions of increasing scope and complexity.
  • Familiarity with, and an active engagement in DevOps, integration and application architecture, data center and systems architecture and design and business capability modelling.
  • Experience transforming detailed architectural views as solutions for critical business functions.
  • Experience in cloud technologies.
  • Track record of maintaining stakeholder business knowledge, goals and annual objectives to anticipate business needs.
  • Exceptional communication skills and the ability to communicate and collaborate appropriately at all levels of the organization. This includes written and verbal communications, as well as visualizations.
  • Strong interpersonal skills, with the ability to navigate across organizational boundaries of architecture, engineering, and operations.
  • Assisting in key capacity and risk metrics reporting.
  • Performing root cause analysis and business impact analysis for incidents related to capacity and scalability, as well as performing application health assessments for application areas considered at-risk for capacity and scalability.

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