Senior Data Scientist

Senior Data Scientist

Location: (Remote eligible within continental U.S.)

Overview:

A dynamic opportunity for a Senior Data Scientist to support a growing AI/ML team focused on developing advanced models to drive business decisions in areas like credit risk, marketing, and banking services. This role bridges data science expertise with business impact, developing scalable solutions, working closely with engineering and analytics teams, and contributing to the evolution of analytical capabilities across the organization.

Key Responsibilities:

• Collect, clean, and analyze structured and unstructured data to develop advanced analytics solutions.
• Design and implement scalable machine learning, simulation, and optimization models to support key business strategies.
• Apply appropriate modeling techniques based on available data, application needs, and business objectives.
• Ensure models are developed in compliance with governance frameworks and validation standards.
• Create and maintain detailed technical documentation and support model reviews and audits.
• Translate complex data-driven insights into actionable business recommendations for stakeholders.
• Manage timelines, risks, and deliverables for analytics projects and escalate issues as needed.
• Collaborate with engineering and IT teams to deploy models into production systems.
• Mentor junior data scientists and contribute to building internal libraries and best practices.
• Stay up to date with evolving data science methodologies, technologies, and regulatory standards.

Qualifications:

• Bachelor’s degree in a quantitative field (Math, Statistics, Computer Science, Economics, etc.) OR 4 additional years of relevant experience in lieu of degree.
• 6+ years of experience in predictive analytics or data analysis OR 4 years with an advanced degree (Master’s or PhD).
• 4+ years of experience in training and validating machine learning or statistical models.
• Strong coding skills in languages such as Python or R.
• Proficient in querying and preprocessing data using SQL, HQL, or NoSQL tools.
• Experience working with various data types, including structured, semi-structured, and unstructured formats (e.g., JSON, XML, images).
• Expertise in supervised and unsupervised modeling techniques (e.g., logistic regression, decision trees, clustering).
• Proven ability to write transparent, well-documented code.
• Strong communication skills to explain technical findings to non-technical stakeholders.
• Understanding of regulatory standards related to model development and validation.

Preferred Experience:

• Prior experience in a medium or large financial institution.
• Advanced knowledge of Python and/or SAS.
• Familiarity with Model Governance and Model Risk Management practices.
• Experience collaborating with compliance and control teams.

Note: This position allows for remote work within the continental U.S. Occasional travel may be required.

Compensation:

$143,320 – $273,930 per year, depending on experience and qualifications.