Data Scientist

• Under limited supervision, the Data Scientist works closely with business stakeholders to understand how data can be used to achieve their goals.
• Designs data modeling processes, creates algorithms and predictive models and helps analyze the data and shares insights.
• Critical thinking and problem-solving skills are essential for interpreting data.
• Must have a passion for machine-learning and research.
• This position will be tasked with helping the company analyze trends to make better data-based decisions.
• Analyzes large amounts of information to discover trends and patterns.
• Designs machine learning models for predictive analytics.
• Presents information using data visualization techniques.
• Undertakes preprocessing of structured and unstructured data.
• Identifies valuable data sources and automates collection processes.
• Performs other duties as assigned.

Data Scientist, Finance

• Manages and builds systems of models to analyze diverse big data sources
• Manages and participates in developing, testing and validating models that drive business value
• Assists with identifying and interpreting insights from data
• Direct leadership of assigned data science team
• Manage and participate in working with large data sets to solve unstructured problems using different analytical and statistical approaches
• Manage the sourcing, ingesting, and cleaning of data sets in preparation for analysis
• Ensure data is stable, accounting for complex data drift in development and production
• Manage the building of econometric, statistical and machine learning models for various problems
• Manage committing of complex coding into model repository
• Lead the selection and refinement of models taking into account performance, reliability and stability metrics
• Develop model refinement educational materials and deliver related training for data users
• Create outputs from multiple models for business discussions
• Lead stakeholder meetings to discuss concerns, opportunities and production challenges
• Review own and assigned team’s code to ensure it is efficient, accurate, and using best practices
• Understand and adhere to the Company’s risk and regulatory standards, policies and controls

Lead Data Scientist – Compliance Analytics

• Use Python or R to explore data, perform analysis, and rapidly prototype analytical approaches within repeatable workflows.
• Design, develop, validate, and monitor interpretable machine learning models using sound statistical and modeling techniques.
• Own the end‑to‑end delivery of analytical solutions—from prototype through testing, validation, and scalable production deployment—collaborating closely with engineering and testing partners to ensure production readiness.
• Act as a key communication bridge across business, product, and engineering teams to gather and document requirements, clearly communicate analytical solutions, and ensure business needs are accurately implemented.
• Define and track performance metrics to measure solution effectiveness and business impact.

Data Scientist – Corporate & Institutional Banking

• Performs analytical tasks on structured and unstructured data to extract actionable business insights.
• Participates in the data gathering, data processing and data mining of large and complex datasets.
• Develops algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.
• Runs analytical experiments in a methodical manner to find opportunities for product and process optimization.
• Assists in the presentation of business insights to management using visualization technologies and data storytelling.
• May partner with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.

Data Scientist, Gen AI Governance

• Provides financial and regulatory reporting and analyses to maintain adequate controls over the financial and regulatory reporting processes
• Responsible for running complex business performance, risk and operational analytics
• Develops analytical methods/models to assess market, credit and/or operational risk of new and existing financial products
• Analyzes large datasets to improve risk adjusted returns, deliver profitable growth, and communicate conclusions
• Synthesizes analytical results to develop strategies that improve lending decisions and manage risk
• Applies predictive models and other tools to develop and execute appropriate segmentation and targeting for acquisition
• Works with business, credit, data, and model development partners to design and monitor test designs and analytical reporting

Fraud Data Scientist – Card Transactions

• Serve as the primary point of contact for At Work-related data and analytics needs
• Partner with CAPTRUST’s centralized data team to prioritize, design, and improve data solutions supporting At Work
• Help establish consistent definitions, metrics, and reporting standards across the At Work practice
• Improve data quality, clarity, and usability over time
• Support and enhance internal and client-facing reporting used by At Work teams
• Work closely with Operations to understand recurring reporting needs and reduce one-off or manual efforts
• Develop dashboards and reports that support operational planning, advisor effectiveness, and leadership decision-making
• Translate reporting outputs into insights that inform action, not just describe activity
• Develop qualitative and quantitative measures of client and participant engagement, trust, and relationship health
• Help establish ongoing feedback loops across the client and participant lifecycle, beyond episodic surveys
• Identify trends that signal strengthening relationships, stagnation, or potential breakdowns
• Support analysis related to the annual financial wellness survey and other experience-related initiatives
• Analyze patterns associated with strong long-term outcomes such as sustained engagement, retention, and expansion of advisory relationships as needs evolve
• Partner with leadership and Operations to identify where additional investment of time or resources may be needed
• Help reduce reliance on anecdotal feedback through clearer, shared insight

Data & Analytics Lead

• Help power the next generation of final-mile logistics.
• Develop advanced models and data systems that leverage location, routing, traffic, and spatial signals to improve delivery success, reduce operational costs, and create a better experience for customers and drivers.
• Work with large-scale GPS traces, mapping data and geospatial datasets.
• Collaborate with product managers, logistic operators and software engineers to turn models into real-world systems.
• Design experiments and translate complex geospatial insights into actionable operational decisions.

• Gather, preprocess, and validate datasets from internal and external sources.
• Identify trends, patterns, and anomalies using statistical and visual techniques.
• Build and evaluate predictive models using machine learning algorithms.
• Create dashboards and visual reports to communicate findings to stakeholders.
• Maintain clear records of methodologies, code, and project outcomes.
• Work closely with cross-functional teams to align data solutions with business needs.

Data Science, AI Intern

• Collaborate with leaders across the organization to develop and execute on a data strategy inline with ActBlue's near and long term goals, including supporting organizational growth through acquisitions and partnerships
• Foster a data centric culture by upleveling our ability to make data-informed decisions and build best in class data products that meet rigorous performance and reliability standards
• Enable and advocate for AI/ML driven products and features across the ActBlue Platform through building scalable machine learning infrastructure that serves production environments and identifying new opportunities to deploy data science and analytics capacity in service of our mission
• Oversee our Data Science, Data Analytics, Data Engineering, and Data Platform teams in a fast-paced, mission-driven environment
• Guide the evolution of our data systems, tools, and architecture to meet the organization's needs, including data consolidation, governance frameworks, and unified data models across multiple entities
• Ensure high-quality communication and a stakeholder-centric approach between our data teams and their internal customers, with an emphasis on responsiveness and partnership during high-stakes moments

Director of Data Science – Engineering

• Develop a breakthrough idea or solution for customer’s pressing problems
• Collaborate with teams in a startup accelerator environment
• Receive mentorship from senior leaders
• Participate in final Challenge Cup presentation

Data Scientist Intern, Summer 2026

• Detecting, analyzing, and mitigating deposit fraud incidents.
• Leading the development and execution of data-driven fraud prevention strategies.
• Collaborating with fraud operations, technology, and product teams to deploy controls effectively.
• Monitoring deposit transaction data to identify emerging fraud patterns and anomalies.
• Developing and refining fraud detection rules using statistical and quantitative/machine learning techniques.
• Mentoring junior analysts within the team, fostering a culture of curiosity, rigor, and innovation in fraud prevention.
• Delivering actionable insights and performance metrics to senior leadership.

Senior Data Scientist – Deposit Fraud Analytics, Strategy

• End-to-end ownership of Search, Recommendations, and Personalization
• Identify high-impact opportunities
• Rapidly prototyping and experimenting (often using AI tools)
• Measuring and iterating based on real business outcomes
• Develop and iterate on models (ranking, recommendation, personalization, etc.)
• Partner with Product, Engineering, and Analytics to bring ideas to life

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