Senior Data Scientist

Senior Data Scientist

Salary Range: $143,320 – $273,930

Position Overview:

An opportunity is available for a Senior Data Scientist to join an AI/ML team focused on delivering scalable machine learning and statistical modeling solutions across areas such as credit risk, marketing, and banking. This role involves translating complex business problems into data-driven solutions that generate real business value through automation, risk reduction, and revenue enhancement.

You will collaborate closely with engineering teams, business stakeholders, and risk managers to deploy and validate models that support customer-facing applications. Candidates with prior experience in large financial institutions or regulated industries are highly preferred.

Key Responsibilities:

• Gather and manipulate structured and unstructured data to create advanced analytics and machine learning solutions.
• Build scalable models using statistical and ML techniques to derive actionable insights.
• Choose appropriate modeling methods based on business needs, data limitations, and technical requirements.
• Develop, validate, and document models within the model development and risk management framework.
• Translate complex business questions into clear analytical problems and communicate findings effectively to non-technical stakeholders.
• Build and maintain reusable, production-ready modeling assets and tools.
• Mentor junior team members and contribute to best practices in model development and deployment.
• Collaborate with cross-functional teams including Data Engineering and IT to deploy and maintain models in production environments.
• Stay current with emerging technologies and modeling techniques.
• Participate in internal technical communities and continuous improvement efforts.
• Ensure compliance with relevant risk and regulatory requirements throughout the model lifecycle.

Qualifications:

Required:

• Bachelor’s degree in a quantitative discipline (e.g., Math, Statistics, Computer Science, Economics, Engineering); or 4 additional years of related experience in lieu of a degree.
• 6+ years of experience in predictive analytics or data analysis; or 4+ years with a Master’s or PhD.
• 4+ years developing and validating models using statistical, machine learning, or simulation techniques.
• Experience in at least one scripting language such as Python or R.
• Proficiency in querying and preprocessing data using SQL, HQL, or NoSQL technologies.
• Ability to work with structured, semi-structured, and unstructured data formats (e.g., JSON, text, images).
• Experience with classical supervised and unsupervised modeling techniques.
• Strong documentation and code transparency practices.
• Ability to explain technical findings and model implications to non-technical stakeholders.

Preferred:

• Experience in medium to large financial institutions.
• Expertise in Python and/or SAS.
• Familiarity with Model Risk Management and regulatory compliance.
• Experience partnering with control and governance teams.
• Background in deploying models in production environments with cloud platforms.

Compensation & Benefits:

• Competitive salary based on experience and market data
• Performance-based incentive pay opportunities
• Comprehensive benefits package including medical, dental, vision, 401(k), pension, life insurance, paid time off, volunteer hours, and wellness programs
• Career path planning and educational support for professional development