Data Scientist

• Define reference architecture for agentic AI solutions
• Establish design patterns for Retrieval-Augmented Generation (RAG), Multi-agent orchestration
• Guide use-case prioritization and platform selection
• Build and deploy production-grade AI agents
• Implement: Prompt engineering, workflows, API integrations
• Establish enterprise AI guardrails, including Security and Data governance
• Configure and deploy Azure OpenAI / model endpoints
• Co-build pilot agents with consultants and internal teams
• Enable internal teams on agent design patterns and Responsible AI practices

Senior Data Scientist

• Manage the production process from concept through completion, ensuring creative quality while coordinating timelines, budgets, and resources
• Drive active data science projects to production — including a Next Best Action engine, customer segmentation model, and comp plan chatbot — defining what "done" looks like and holding the team accountable to shipping
• Establish a delivery cadence that balances exploration with execution, mentoring data scientists toward outcome-oriented habits: scoping work to what can be shipped, documenting what was built, and handing off cleanly
• Own the AI activation layer — ensuring data and models reach business users through practical surfaces, including Copilot, Fabric Agents, Power Automate flows, and Emarsys integrations
• Configure and optimize Microsoft Fabric semantic models for AI consumption and build MCP server integrations between Fabric and Claude (or equivalent) to make USANA's data accessible within internal AI tools
• Set technical direction for applied AI and ML — recommendation systems, customer segmentation, predictive churn, and intelligent automation — ensuring models are understood end-to-end from development through production handoff
• Partner with executive and commercial stakeholders to identify high-impact AI opportunities, translating complex technical concepts into actionable business strategies while championing responsible AI practices
• Collaborate cross-functionally with BI, marketing, data engineering, and IT teams to deliver end-to-end solutions built on trusted, well-governed data from USANA's Snowflake medallion architecture
• Define standards for model lifecycle management, feature engineering, and AI integration patterns — and stay current on the Microsoft AI ecosystem to evaluate emerging tools for strategic adoption

AI Activation, Data Science Manager

• 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

• 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

• 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

• Bridge the gap between complex datasets and strategic action.
• Synthesize information from various external sources to develop visibility and insights into search recall gaps and emerging topic trends.
• Inform Wikimedia’s strategy for ensuring that people continue to find the content they need.
• Integrate fragmented data to create a unified view of how users discover and use content.
• Translate analytics and complex trends into actionable narratives.
• Develop automated systems to detect under-indexed content.
• Establish metrics and frameworks for content utilization within Large Language Models.
• Collaborate with product leaders to set goals and track success.
• Assess efficacy of new initiatives through experiment design and analysis
• Interpret website performance data to inform UX/UI enhancements.

Senior Data Scientist, Ecosystems

• Improve the geochemical data ecosystem at Zanskar, including automating steps of the data ingestion workflow
• Building data pipelines where needed
• Designing visual data displays
• Developing machine learning models leveraging geochemical data to uncover hidden geothermal systems and drive real-world exploration decisions
• Close collaboration with research, engineering, geoscience, land, and field teams

Data Scientist – Prospect Generation

• Contribute to creating best practices for the team
• Initiate and drive collaboration with stakeholders, architects, and data engineers to discover, define, cleanse, and refine the data needed for analysis and modeling
• Analyze large and novel datasets to extract actionable insights to inform model development and understand consumer behavior
• Inform experimental design to formulate solutions addressing major business challenges and innovation opportunities
• Build models using a variety of statistical and machine learning techniques, from selecting the best type of model for the problem to using techniques to measure and optimize model performance
• Prepare models for production deployment and monitoring of performance over time
• Embrace and uphold Ibotta’s Core Values of Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere

Data Scientist, Client Data & Measurement

• Provide leadership/direction to ensure technology initiatives and opportunities for process improvements are systematically identified, pursued, and supported.
• Develop architectures and concepts for advanced digital technologies with a focus on implementation within Northrop Grumman
• Interact with customers (internal and external)
• Reach out and work with colleges, universities, government, supplier as part of development and improvement projects
• Introduce and develop new technologies for the manufacturing floor
• Lead projects consisting of cross functional teams of high performing engineers developing advanced systems designs and concepts.
• Provide technical leadership and oversight to achieve efficient, effective, and innovative Engineering solutions
• Apply new technologies as well as common designs and products enabling rapid development, prototyping and affordable solutions.

Senior Staff Data Scientist

• Responsibilities may vary by assignment depending on department and need. The Intern receives assignments from supervising staff.
• The Manager reviews the Intern's work occasionally.
• The supervisor reviews each assignment as it is completed.
• The Intern is expected to meet rigid and challenging deadlines, work in harmony with other people, take direction on each assignment, and give full attention to detail.
• Independence in working, tact, and diplomacy are required.
• Sound judgment of Church doctrine, history, organization, policy and protocol are also expected.

Data Scientist – Intern

• Help lead the continued evolution of Ibotta's measurement methodology through exploration of cutting-edge measurement research and experimental design
• Collaborate as the go-to troubleshooter for measurement anomalies—exploring outlier results, diagnosing data quality issues, and validating statistical assumptions across alpha, beta, and production measurement systems
• Lead code reviews and architecture discussions, providing expert guidance on design patterns, scalability, and technical trade-offs
• Foster a culture of code quality, rigorous measurement, and collaborative problem-solving
• Evaluate and adopt new tools, explore frameworks and innovative model forms that enhance team effectiveness, while maintaining code quality standards
• Lead enterprise-wide data science initiatives spanning 6+ months with measurable business impact across multiple teams and KRs
• Build trusted partnerships with C-suite executives, product managers, and data science leaders to translate business problems into technical solutions while delivering with consistency and transparency
• Present complex technical concepts clearly to both technical and non-technical audiences, including executive leadership
• Deliver high impact presentations on key initiatives and research, with easily understood visualizations, to drive insight and adoption
• Mentor more junior data scientists through technical guidance, code reviews, and strategic coaching
• Create technical training programs and documentation that elevate organizational data science maturity
• Embrace and uphold Ibotta's Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere

Principal Data Scientist, Causal Inference

• Architect and develop scalable ML and AI solutions, aligning model design and deployment with product and customer needs.
• Build, train, and optimize machine learning models using Python, ML frameworks, and large‑scale data pipelines.
• Leverage PyTorch, ML SDKs, and GPU‑accelerated workflows to support advanced model development and experimentation.
• Work with large, complex datasets to design robust feature engineering, data processing, and model evaluation approaches.
• Collaborate cross‑functionally with engineering, analytics, finance, and professional services stakeholders to deliver end‑to‑end ML solutions.
• Participate in the design of ML system architecture, ensuring reliability, quality, and operational efficiency.
• Research emerging AI/ML technologies and integrate new capabilities that strengthen Epicor’s long‑term data science strategy.

• 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.

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Data Scientist, Client Data & Measurement

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Data Scientist – Intern

Principal Data Scientist, Causal Inference

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