Data Scientist

• Provide technical leadership across the Analytics function
• Create, develop, and maintain AML typologies
• Collaborate with cross-functional teams and support Financial Intelligence Units (FIU)
• Oversee the execution of multiple projects
• Ensure successful project completion within established timelines

Data Scientist – FCRM

• Lead the design, development, and deployment of advanced statistical, machine learning, and AI solutions—including LLM-powered applications—to solve complex business, workforce, and organizational challenges.
• Translate ambiguous business and HR questions into well-defined analytical approaches, scalable data products, and decision-support tools.
• Design and oversee end-to-end data science workflows, including data extraction (e.g., enterprise data warehouses), validation, modeling, deployment, and performance monitoring.
• Integrate data from multiple internal and external sources to create modeling-ready datasets, reusable data assets, semantic layers, and metadata frameworks that enable scalable and self-service analytics.
• Develop and productionize predictive and prescriptive models to explain outcomes, forecast behavior, and identify risks and opportunities.
• Build and deploy advanced AI solutions using modern frameworks (e.g., LLMs, embeddings, RAG architectures), and lead experimentation and rapid prototyping to evaluate emerging capabilities.
• Embed analytics and AI solutions into business processes through automation, system integration, and near real-time data capabilities.
• Partner with HR Business Partners, talent leaders, executives, data engineering, and IT teams to deliver actionable insights and ensure alignment with architectural, security, and data quality standards.
• Provide technical leadership across data science initiatives, ensuring consistency with best practices, methodologies, and quality standards.
• Communicate complex analytical insights and AI concepts clearly to non-technical stakeholders, influencing strategic and operational decision-making.
• Mentor and coach junior team members, elevating team capabilities in AI, machine learning, and analytics best practices.
• Ensure adherence to responsible AI principles, including data privacy, bias mitigation, security, and ethical use of employee data.
• Stay current on emerging AI and analytics trends, proactively identifying opportunities to incorporate new technologies into enterprise use cases.

Senior Data Scientist – AI, People Analytics

• Partner with Marketing to Define and Solve Problems – Work closely with marketing stakeholders to understand business challenges, define success metrics, and translate needs into analytical approaches that drive performance across campaigns and channels.
• Design and Deliver Data-Driven Solutions – Apply statistical analysis and machine learning to develop solutions that address business needs, then present findings, influence decisions, and gain alignment on adoption.
• Lead Experimentation and Optimization – Develop and manage testing frameworks (A/B testing, campaign experimentation) across channels and markets. Analyze results and provide clear recommendations to improve performance and inform future strategy.
• Translate Results into Business Impact – Clearly communicate insights and quantify outcomes (e.g., campaign performance lift, engagement improvements, ROI) to ensure stakeholders understand the value and take action.
• Partner to Operationalize Solutions – Collaborate with Technology and Engineering teams to transition validated models into production, supporting implementation through scalable pipelines and processes.
• Influence Through Storytelling – Present insights and recommendations to both technical and non-technical audiences, including senior stakeholders, to drive alignment and decision-making.

Senior Data Scientist – Marketing Analytics

• Lead a team of business data analysts responsible for implementation, enhancement, and maintenance of AML Transaction Monitoring platform
• Bring strong domain expertise in Securities Compliance and understand transaction patterns in trading
• Collaborate with Technology, Data, and Modeling teams for end-to-end delivery
• Ensure engagement with Audit and Compliance stakeholders to support issue validation

AML Business Data Manager

• Collect data and use data science techniques to uncover insights
• Provide oversight and consultative advice as the lead Data Scientist
• Evaluate technical solutions and lead innovation to solve complex business issues
• Provide strategic and day-to-day direction on CTR program activities
• Coordinate with internal and external stakeholders for audits and examinations

Lead Data Scientist

• 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

• Lead the analytics center of excellence for Gainsight's GTM organization, with an initial focus on Sales and Customer Success
• Set standards for dashboard design, metric definitions, data governance, and insight delivery across the team
• Own the quality and trust of all GTM reporting, ensuring leadership can rely on the numbers without second-guessing them
• Act as a mentor to peer analysts, focused on technical and business acumen, escalation support, knowledge and skills sharing
• Own end-to-end analytics across bookings, pipeline health, forecasting, GRR, NRR, renewals, and customer expansion
• Partner with the GTM Planning team on evolution of planning models that support AOP, quota setting, capacity planning, and scenario analysis
• Deliver executive-ready dashboards and weekly/monthly/quarterly operating cadences for Sales and CS leadership
• Partner with Finance on bookings-to-revenue reconciliation and board-level reporting
• Proactively surface risks and opportunities, moving from answering questions to anticipating them
• Lead the transformation from static BI dashboards to AI-enabled, self-service data exploration for GTM stakeholders
• Partner with the GTM Data Architect to establish the semantic layer — the business-side definitions of ACV, GRR, pipeline, and churn that enable reliable AI querying
• Design and deploy AI-powered analytical workflows including natural language querying, anomaly detection, and proactive insight surfacing
• Enable Sales and CS leaders to query data independently without routing every question through the analytics team
• Stay current on the evolving landscape of AI analytics tooling and bring forward recommendations
• Serve as a trusted analytical thought partner to Sales VPs, CS leadership, and RevOps
• Translate complex data into clear business recommendations, connecting the numbers to the "so what"
• Support strategic planning processes including territory design, AOP, and Rules of Engagement

Senior Revenue Analytics Lead

• Design, build, and own end-to-end machine learning models and AI-powered solutions, from problem framing through production deployment and impact measurement, focused on driving customer retention and operational excellence
• Develop and enhance AI-driven tools that deliver explainable, actionable insights to Customer Success and Renewals teams, enabling data-informed decisions that protect and grow revenue
• Partner closely with Customer Success, Renewals, Product, and Engineering to translate complex business challenges into well-scoped data science initiatives aligned to high-impact retention opportunities
• Evaluate, prototype, and implement emerging AI/ML approaches, including generative AI and agentic workflows, to improve team efficiency and stakeholder value in a rapidly evolving landscape
• Mentor and support fellow Data Scientists by setting high standards for analytical rigor, code quality, and documentation while contributing to best practices and team growth

Senior Data Scientist, Customer Care

• 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

Senior Business Data Scientist, Marketing Analytics

• Own the proprietary model flywheel with 90M+ assigned programs and build a proprietary therapeutic AI model
• Lead AI product delivery across all AI bets and drive design, development, deployment, and continuous improvement of AI systems
• Define and execute the AI/ML technical roadmap by collaborating with Product and Content to prioritize clinical and product needs
• Establish trust-by-design as a standard by ensuring transparency and auditability in all AI features
• Own the clinical AI safety and quality framework, ensuring HIPAA-compliant data handling alongside Legal
• Drive cross-functional alignment and work closely with various teams to embed AI in workflows
• Continuously evaluate emerging developments in LLMs and clinical AI for practical advantages

Head of Data and Machine Learning

• Support the Pricing Strategy team by analyzing pricing, financial, and competitive data
• Build analytical insights and support pricing initiatives
• Collaborate with cross-functional partners including Pricing, Marketing, Sales, Product, Finance, and Analytics teams
• Analyze pricing across products and customer segments
• Develop and enhance pricing logic and build reports or dashboards to track pricing performance

Pricing Strategy Analyst, Data Science

• 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

• Identifies business trends and problems through complex data analysis.
• Interprets results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining independently.
• Designs, develops, and implements the most valuable business solutions for the organization.
• Leverage skills in handling very large datasets to perform exploratory analysis, construct relevant variables, and perform sample design
• Build and improve upon already built, complex predictive models from multiple sources to substantially improve business operations
• Automate feedback loops for algorithms/models in production and create repeatable processes and scalable data products
• Act as technical expert to recommend and develop innovative analytic solutions
• Communicate and present results to internal audiences, prepare presentations and documentation of models and analytical solutions
• Influence functional teams and develop best practices across the organization
• Other duties as assigned

Senior Data Scientist

• Lead the development of advanced statistical, machine learning, and AI solutions that support strategic and operational decision-making.
• Apply domain and business expertise to translate complex problems into well-defined analytical approaches and scalable solutions.
• Design and oversee end-to-end data science workflows, including data extraction, validation, modeling, deployment, and performance monitoring.
• Integrate data from multiple internal and external sources to produce modeling-ready datasets and reusable data assets.
• Build predictive and prescriptive models to explain outcomes, forecast behavior, and identify risk or opportunity.
• Play a lead role in embedding analytics and AI solutions into existing business processes through automation and system integration.
• Partner with data engineering, IT, and business teams to ensure solutions meet architectural, security, and quality standards.
• Provide technical leadership across data science initiatives, ensuring consistency with agreed-upon methodologies and quality attributes.
• Communicate analytical results and implications clearly to leaders, enabling informed decision-making.
• Coach and mentor less experienced data scientists; provide guidance on prioritization, approach, and technical execution.
• Ensure adherence to responsible AI standards, including privacy, bias mitigation, and ethical use of employee data.
• Maintain awareness of emerging analytics and AI techniques and evaluate applicability to enterprise use cases.

• Support data collection, cleaning, transformation, and exploratory analysis for ongoing projects.
• Assist in developing, testing, and improving machine learning and LLM models.
• Perform deep-dive analysis to evaluate model behavior, output quality, and performance across different approaches.
• Help refine prompts, evaluation criteria, and testing workflows to improve consistency and outcomes.
• Partner with cross-functional teams to translate business questions into analytical solutions.
• Build reports, visualizations, and dashboards to communicate insights to technical and non-technical stakeholders.
• Document methods, experiment results, and recommendations clearly and thoroughly.
• Participate in team meetings, project discussions, and implementation reviews.

See all jobs on JobTailor

Data Scientist – FCRM

Senior Data Scientist – AI, People Analytics

Senior Data Scientist – Marketing Analytics

AML Business Data Manager

Lead Data Scientist

Data & Analytics Lead

Senior Revenue Analytics Lead

Senior Data Scientist, Customer Care

Data Science, AI Intern

Senior Business Data Scientist, Marketing Analytics

Head of Data and Machine Learning

Pricing Strategy Analyst, Data Science

Data Scientist Intern, Summer 2026

Senior Data Scientist

Senior Data Scientist – AI, People Analytics

Innovation, Data Science Internship