• Lead the strategy, roadmap, and execution for Data, Analytics, AI, Automation, and Innovation across the enterprise. • Establish enterprise data governance, architecture, engineering, analytics, and business intelligence capabilities that enable data-driven decision-making. • Lead AI strategy, governance, adoption, and value realization, including Generative AI, Agentic AI, Microsoft Copilot, Machine Learning, and Intelligent Automation. • Identify, prioritize, and deliver high-value AI and automation use cases that improve productivity, operational efficiency, customer experience, and business performance. • Evaluate and scale emerging technologies and innovation initiatives that support digital transformation and competitive advantage. • Partner with leaders across Architecture, Application Development, Infrastructure, IT Operations, and Cybersecurity to ensure alignment with enterprise technology strategies and modernization efforts. • Build and lead high-performing teams while fostering a culture of innovation, accountability, and continuous improvement. • Serve as a trusted advisor to executive leadership on technology-enabled business transformation and investment decisions. • Ensure compliance with security, privacy, governance, regulatory, and responsible AI requirements.

• Lead the design, development, testing, validation, and deployment of advanced analytics and machine learning solutions. • Manage analytics projects supporting fraud detection, fraud prevention, waste and abuse identification, and investigative activities. • Develop and evaluate predictive models, anomaly detection methods, risk models, and entity-resolution techniques. • Lead the development of analytics solutions using artificial intelligence, machine learning, natural language processing, graph analytics, and data visualization. • Identify and refine analytics use cases in collaboration with government stakeholders, investigators, and program teams. • Translate business, investigative, and operational requirements into technical analytics solutions. • Lead technical discovery, data assessment, feature development, model selection, and solution design activities. • Evaluate model performance, identify gaps, and recommend refinements or recalibration as needed. • Ensure analytics models and outputs are accurate, explainable, defensible, repeatable, and aligned with project objectives. • Track project progress, risks, issues, dependencies, and quality-control activities. • Conduct technical reviews and quality-control reviews of analytics work products before delivery. • Review code, models, documentation, data transformations, and analytic outputs for accuracy and completeness. • Support the deployment, monitoring, maintenance, and ongoing improvement of analytics models in production environments. • Collaborate with data engineers and data-management teams to support data ingestion, preparation, governance, quality, and lineage. • Develop and maintain technical documentation describing methodologies, data sources, model designs, assumptions, findings, and limitations. • Present analytical findings, technical recommendations, and project updates to technical and non-technical stakeholders. • Provide technical leadership, mentoring, and guidance to data scientists, analysts, and other project personnel.

• Partner with agency stakeholders to gather requirements and define analytics and reporting needs • Assess and prepare data from multiple systems for analytics and reporting use cases • Design and develop operational and decision-support dashboards that drive action • Translate program workflows and policy into clear metrics, KPIs, and reporting logic • Build and publish user-centered data products that are accessible and meaningful to business users • Advise stakeholders on opportunities to expand the role and impact of data across the agency • Collaborate across program, policy, and technical teams to align reporting with business priorities

Role Description You'll be joining the data feeds part of our organization, focusing on Kepler, a tractions feed that tracks over $45 billion in US consumer transactions across 600+ merchants and 200+ tickers. As a Data Analyst for Kepler, you'll ramp quickly and build deep expertise in our third-party and proprietary datasets and methodologies. Working closely with customers, Product, Data Science, and Engineering, you'll take full ownership of the Kepler data — ensuring accuracy, improving methodologies, implementing QA frameworks, and prototyping enhancements that engineering will turn into robust, reliable data pipelines. This is a role for someone who wants to go deep on hard analytical problems, takes pride in getting the details right, and is motivated by owning work that matters. You'll work cross-functionally with teams across the organization to deliver best-in-class outputs. You'll also be expected to bring ideas, not just execute on others. This is a remote-friendly opportunity that can sit in NYC (where our headquarter is located), one of our office hubs, or anywhere else in the US. - Own Kepler data content end-to-end — driving product success by delivering best-in-class outputs with a focus on accuracy, and continuously increasing client value. - Work with massive amounts of data and develop deep expertise in our proprietary methods and techniques, building strong mental models that allow you to ensure data accuracy, identify methodology gaps, and derive key insights. - Tackle complex data problems using strong analytical judgment to refine methodologies, test new datasets, and solve challenges that require creative thinking — even when information is incomplete or ambiguous. - Use AI and tooling to drive meaningful leverage — increasing speed, reducing manual work, and automating portions of workflows. You'll build repeatable processes, maintain a high bar for correctness and quality, and validate AI-generated outputs. - Use AI to drive client-value — you will write prompts and run automated evaluation processes to ensure our client-facing Kepler Insight Agent is accurate and able to answer the questions our customers are asking. - Collaborate cross-functionally with Research, Engineering, and other teams — coordinating across functions to unblock work, align on best practices, and develop solutions that streamline workflows and optimize data processes. - Help our customers understand the data by handling high-complexity questions about anomalies and trends in the data that our first line of support can’t handle. Qualifications - 4-6+ years of experience in data analytics, with a background in fields like financial services, management consulting, data science, or high-growth technology. - Expert fluency in SQL and experience using Python or PySpark, including building reliable, reusable analysis workflows. - A proven track record of quickly learning complex data methodologies and building strong mental models of how and why data works. - Experience leading complex, ambiguous projects with multiple stakeholders — scoping the approach, driving alignment, and delivering outcomes. - Ability to clearly communicate complex concepts — including methodology, risks, and tradeoffs — and influence cross-functional partners to move decisions forward. - Active use of AI tools and excitement about using AI to drive leverage. Requirements - Strong analytical judgment and problem-solving skills. - Experience with data accuracy and methodology refinement. - Ability to work cross-functionally and collaborate effectively. Benefits - Flexible work hours and flexible vacation. - Generous 401K match and parental leave. - Team events and wellness budget. - Learning reimbursement. - Compensation package includes a competitive salary, with an anticipated annual base compensation of $165K-$185K. - Opportunity for remote work within the United States.