Scientist Jobs

About The Position

Requirements

• Bachelor’s degree in Computer Science, Mathematics, Statistics, Business Analytics, Data Science, or a related quantitative discipline, or equivalent relevant experience substituted for the degree.
• At least 7 years of progressive experience in analytics, data science, or quantitative analysis.
• At least 3 years of experience with SAS, SQL, Python, and/or R for statistical analysis and modeling.
• At least 3 years of experience applying machine-learning techniques in professional environments.

Nice To Haves

• Master’s degree.
• Experience supporting analytics solutions within modern data platforms such as Snowflake, Databricks, BigQuery, or Redshift.
• Financial services or other regulated-industry experience.

Responsibilities

• Design, develop, and maintain advanced analytical and data science solutions that support business strategy and operational decision-making.
• Apply statistical and AI/machine-learning techniques to business problems such as segmentation, targeting, forecasting, and optimization.
• Manipulate, model, and analyze large, complex datasets using Python, SQL, and related tools to produce reliable, scalable insights.
• Contribute to repeatable and scalable analytics solution frameworks that operationalize data science models.
• Partner with data engineering teams on data pipelines, model integration, and analytics workflows.
• Support experimentation, pilots, and minimum viable products aligned with defined business use cases.
• Translate complex and disparate data sources into clear data stories that enable data-informed decision-making.
• Develop executive-ready dashboards, visualizations, and analytical summaries using tools such as Power BI.
• Prepare recurring and ad hoc analyses, reports, and presentations for management decisions, committee reviews, and enterprise information requests.
• Ensure analytical work products comply with applicable standards, policies, regulations, and internal controls.
• Monitor internal and external economic, market, and industry trends that may influence business outcomes.
• Identify opportunities to improve analytics methods, tools, and processes, and stay current on analytics, risk modeling, AI, and machine-learning practices.
• Design and evaluate experiments, tests, and proofs of concept to assess analytical approaches, tools, and technologies.
• Identify opportunities to automate, streamline, or improve analytical and risk processes through better data and modeling solutions.
• Collaborate with product managers, analysts, engineers, and other stakeholders to deliver analytics solutions.
• Provide guidance and informal mentorship to analysts on technical problem-solving and analytics best practices.
• Contribute as a subject-matter resource within the Enterprise Reporting and Analytics team.

Benefits

• Market-competitive and internally equitable total rewards compensation package.
• Comprehensive compensation package.
• Well-being and work-life balance programs.
• Career development and growth.
• Rewards and recognition.
• Commitment to Diversity, Equity and Inclusion.