Enterprise Reporting and Analytics - Data Scientist
About The Position
The Data Scientist applies advanced analytics, data science, and quantitative techniques to transform complex enterprise data into actionable insights that support strategic initiatives, product decisions, and business performance. The role partners with business leaders and analytics peers to develop sophisticated analytical solutions and communicate clear, executive-ready insights that inform decision-making, forecasting, and the advancement of the organization’s analytics capabilities. The position develops and maintains analytical and data science solutions, applies statistical and AI/machine-learning techniques to business problems, and analyzes large datasets using tools such as Python and SQL. It contributes to scalable analytics frameworks and works with data engineering teams on pipelines, model integration, and workflows. The role also delivers dashboards, reporting, presentations, and analysis; supports experimentation and pilots; ensures compliance with applicable standards and controls; and identifies ways to improve analytical methods, tools, and processes. It provides technical guidance to analysts and contributes subject-matter expertise within the Enterprise Reporting and Analytics team.
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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
