Data Scientist

• Develop, implement, and deploy machine learning models and statistical analyses to optimize energy storage and solar asset performance across Stem's portfolio
• Design and build data pipelines to extract, transform, and analyze large-scale datasets from energy systems
• Collaborate with software engineering, product management, and energy experts to integrate data-driven solutions into PowerTrack platforms
• Create data visualizations, dashboards, and reports to communicate insights and recommendations to stakeholders
• Conduct exploratory data analysis to identify trends, patterns, and opportunities for improving system performance and business outcomes

Data Scientist, Forecasting – Energy Storage System Optimization

• 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 the development of predictive models for finance use cases
• Build and implement scalable, production-grade analytical models that integrate with enterprise finance systems and data platforms
• Develop, test, and deploy intelligent agents in a Snowflake environment
• Partner closely with Finance business stakeholders, Data Engineering, and UX teams
• Provide technical leadership and mentorship to junior data scientists

Staff Data Scientist

• Leads, develops, and grows a high-performing team of data scientists and machine learning engineers focused on clinical analytics, risk adjustment, and AI/ML model development; sets technical direction, mentors team members, and builds bench strength across statistical modeling, machine learning, and clinical domain expertise.
• Oversees the design, development, and deployment of advanced predictive models, machine learning algorithms, and AI solutions that evaluate clinical scenarios, forecast member risk and outcomes, and identify opportunities to improve quality of care and risk score accuracy.
• Directs data science initiatives leveraging data mining, statistical modeling, natural language processing, and machine learning techniques across clinical, claims, pharmacy, lab, and member-reported data sources.
• Establishes the team's technical standards and best practices for model development, validation, documentation, monitoring, and retraining, ensuring models are explainable, reproducible, and aligned with regulatory and organizational requirements.
• Applies deep expertise in clinical analytics and risk modeling (e.g., HCC/CMS-HCC, condition prevalence, cost and utilization prediction, readmission risk, care gap identification) to deliver models that drive measurable business and clinical impact.
• Develops analytical frameworks, key metrics, and performance dashboards to monitor model performance, clinical quality, risk adjustment outcomes, and operational efficiency.
• Partners with executives, clinicians, actuarial, finance, IT, and business stakeholders to understand priorities, frame analytical problems, and deliver data-driven solutions that inform enterprise strategy.
• Delivers presentations and consultative briefings to senior leadership and cross-functional partners, translating complex modeling concepts and results into clear, actionable recommendations.
• Communicates with leaders to introduce and operationalize incremental KPIs and modeling capabilities that contribute to revenue accuracy, medical cost management, and quality performance targets.
• Establishes and enforces adherence to data governance, model risk management, privacy, and compliance policies, and educates team members on data science and modeling best practices.

Lead Director – Clinical Risk Data Science

• 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

• 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

• To develop and manage predictive modeling assignments through completion; to communicate results; to make recommendations to management; and to ensure model ownership, implementation, and monitoring; to spot trends and to gain maximum insight that can give the company a competitive advantage.
• Develops, prepares, and manages predictive models through completion.
• Identifies required resources; researches data, procedures, and history for a thorough understanding of project direction.
• Collects new data and statistics from multiple sources and generates statistical analysis.
• Collaborates with data management team to develop, refine, and scale data management and analytics procedures, systems, workflows, best practices, and other issues.
• Partners with both business and IT leaders to influence how the organization approaches and meets business challenges of an evolving customer base and changing marketplace, using strong business acumen.
• Prepares reports using various system programs and coordinating with other departments.
• Develops and trains the data management team on new or updated procedures as needed.

• Partner with the payments team by translating the business needs to design and develop core tables, build dashboards, define metrics
• Perform strategic analysis and research to identify new opportunities where business can be improved
• Create data visualizations to translate analytic results for broad understanding across the business
• Build scalable automation solutions using SQL, dashboards, and other tools to create leverage for yourself and the payments team

Senior Data Scientist, Payments

• Utilize advanced mathematical and statistical methods to solve business problems under the supervision of senior data scientists
• Execute exploratory data analysis to validate and quantify trends identified by partner organizations.
• Develop insights, visualizations, and other data artifacts that support broader data science initiatives
• Wrangle and analyze large structured and unstructured datasets in a highly repeatable fashion
• Demonstrate strong communication skills (both written and verbal) and a positive, solution-oriented attitude

Data Scientist, Decision Sciences Team

• 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.

Innovation, Data Science Internship

• Lead and advise on data science and AI content for federal, state, and local government and commercial RFP responses, offering technical expertise and strategic framing that set Cayuse proposals apart in competitive procurements.
• Identify data and AI opportunities in ongoing activities and RFP responses across service lines.
• Review and strengthen civil services and commercial RFP responses for data and AI relevance, identifying opportunities where Cayuse's workforce model and mission create competitive differentiation.
• Work closely with Cayuse’s Proposal Center of Excellence to create reusable proposal frameworks, capability narratives, and case study content that reduce response effort and improve consistency across bids.
• Perform a leadership role in the Atlanta commercial and State government markets, identifying opportunities and working with Commercial and Civil BU’s to capture market share.
• Serve in an advisory role to Cayuse's Business Unit Executives and BU senior leadership regarding data and AI capability roadmap development, tooling decisions, and the sequencing of investments needed to build a scalable data and AI consulting practice.
• Design and deliver internal AI training programs customized for each Cayuse service line and include practical case studies.
• Coordinate, develop and deliver AI literacy sessions for Umatilla Indian Reservation students, translating the practical importance of data and AI into terms that resonate with the communities Cayuse supports and the workforce it is building.
• Speak at conferences and client events on topics such as data strategy, AI adoption, Responsible AI, and workforce reskilling to increase Cayuse's visibility as a trusted data and AI resource in the markets it serves.
• Represent Cayuse as needed in strategic client conversations and executive briefings, providing technical credibility.

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