Data Scientist

Supports a financial services organization by applying advanced data science and machine learning techniques to solve complex business problems using large-scale datasets. Focuses on end-to-end feature engineering, model development, and production-quality code in a fast-paced, collaborative environment. Partners closely with product and engineering teams to uncover trends, improve algorithm performance, and drive data-informed decisions.

• Independently analyze and aggregate large, complex datasets to identify anomalies that affect model and algorithm performance
• Own the full lifecycle of feature engineering, including ideation, development, validation, and selection
• Develop and maintain production-quality code in a fast-paced, agile environment
• Solve challenging analytical problems using extremely large (terabyte-scale) datasets
• Evaluate and apply a range of machine learning techniques to determine the most effective approach for business use cases
• Collaborate closely with product and engineering partners to identify trends, opportunities, and data-driven solutions
• Communicate insights, results, and model performance clearly through visualizations and explanations tailored to non-technical stakeholders
• Adhere to established standards and practices to ensure the security, integrity, and confidentiality of systems and data

• Bachelor’s degree in Mathematics, Statistics, Computer Science, Operations Research, or a related field
• At least 4 years of professional experience in data science, analytics, engineering, or a closely related discipline
• Hands‑on experience building data science pipelines and workflows using Python, R, or similar programming languages
• Strong SQL skills, including query development and performance tuning
• Experience working with large-scale, high-volume datasets (terabyte-scale)
• Practical experience applying a variety of machine learning methods and understanding the parameters that impact model performance
• Familiarity with common machine learning libraries (e.g., scikit‑learn, Spark ML, or similar)
• Experience with data visualization tools and techniques
• Ability to write clean, maintainable, and production-ready code
• Strong interest in rapid prototyping, experimentation, and proof‑of‑concept development
• Proven ability to communicate complex analytical findings to non‑technical audiences
• Ability to meet standard employment screening requirements

Mid‑Senior level

Full‑time

Information Technology

Financial Services, IT Services, IT Consulting