Role Description IXIS is seeking an energetic and curious professional to fill the position of Data Analyst for the company. The core responsibilities for this role include: - Exploring analytics and marketing data to answer client questions. - Collaborating with the Data Science team to perform quantitative analyses. - Summarizing key findings and strategic recommendations for our clients. We are looking for someone with a passion for telling stories through data to join us in a small, high-performance, cross-functional environment. Qualifications - B.A./B.S. (preferably in a quantitative discipline). - 2+ years’ experience in a full-time position in a related role preferred, but not required. - Uncompromising attention to detail and a systematic approach to problem-solving, with good data intuition. - Experience with programmatic data analysis (preferably in R, Python, and/or SQL), with a strong interest in continuing to develop these skills. - Experience with classical statistics, including experimental design and hypothesis testing. - Intellectual curiosity and initiative – always looking for ways to improve current products and processes. - Superb writing skills in both non-technical client communications and technical documentation. Requirements - Conduct exploratory analyses that combine disparate data sources, develop clear data visualizations, and generate narrative takeaways for both ad-hoc and recurring reporting needs. - Improve existing report templates, including narrative structure, look and feel, and data visualizations, with an emphasis on reproducible workflows (such as Git). - Gather qualitative and quantitative research findings to build supporting evidence for retail and digital strategies. - Collaborate with developers, data scientists, data engineers, strategists, and other technical and non-technical stakeholders to continually iterate on data products and other deliverables. - Develop repositories to enable reproducible programmatic data analysis. - Maintain clear lines of communication with supervisor, team, and clients. Benefits - Experience with digital analytics (such as Google Analytics or Adobe Analytics) and e-commerce fundamentals is a plus. - Experience pulling data from APIs and database connections is a plus. - Agile/scrum project management experience is a plus. - Experience in digital marketing is a plus.

• Deliver ad-hoc and recurring analyses supporting Sales, Business and Technical Operations (Salesforce Admins), Revenue, Sales Enablement, Support, and other internal teams, with minimal supervision • Produce core revenue and customer-lifecycle reporting — including month-to-date, quarter-to-date, and trailing-twelve-month metrics — with validation logic that reconciles outputs against source-of-truth figures • Author complex SQL in BigQuery using multi-CTE pipelines, window functions, user-defined functions, and array aggregation, and build reusable views for data aggregation and downstream consumption • Build and refine segmentation and clustering models in BigQuery ML, including feature engineering, look-alike discovery, and cluster profiling, and operationalize model output into actionable deliverables for go-to-market teams • Size addressable-market and ideal-customer opportunities by identifying accounts whose profile fits specific products, and quantify whitespace and upsell potential to support Sales Enablement and account prioritization • Perform entity resolution across multiple source systems using fuzzy matching, normalization, and confidence scoring, reconciling records across platforms • Develop and maintain Tableau dashboards for key business metrics, and lead migration from legacy datasets and BI tools with documented data lineage, custom measures, and visual mappings • Maintain current knowledge of data sources and ongoing data warehouse developments, adapting models and reporting as schemas and requirements change • Translate ambiguous and evolving requests from a wide range of stakeholders into concrete reporting specifications • Contribute to a culture of data discipline, continuous improvement, and analytical excellence across the Revenue Operations organization

• Provide technical data extraction, management, integration, and advanced analytic support including analytic approaches to examine relationships between implementation processes and program outcomes. • Extract APR and performance measurement data; Develop structured analytic datasets; Standardize and harmonize variables across reporting cycles; Maintain documentation of extraction procedures. • Conduct systematic data cleaning and validation; Identify missing or inconsistent data; Implement reproducible validation scripts; Document data quality issues and corrective actions. • Compile DPRP encounter-level datasets; Conduct descriptive and longitudinal analyses; Analyze engagement and outcomes; Generate standardized outputs. • Compile ADA and ADCES datasets; Harmonize data elements; Conduct cross-site comparative analyses; Assess reach and outcomes. • Identify relevant national datasets (as directed); Acquire and integrate secondary datasets; Conduct comparative and contextual analyses; Document limitations and assumptions; Apply analytic methods to assess how implementation factors (e.g., reach, fidelity, adaptation) influence outcomes. • Perform other duties as required.

• Own and continuously improve the company's performance management framework. • Lead company-wide OKR planning, tracking and quarterly review cycles. • Design and implement scalable people processes that improve organizational effectiveness. • Analyze people, performance and operational data to identify trends, measure outcomes and recommend improvements. • Build dashboards and reports that provide meaningful insights into organizational performance. • Define business requirements for HR systems, reporting tools and workflow automation. • Partner with leaders across the company to improve team performance and execution. • Develop frameworks for performance reviews, calibration, promotions and career development. • Drive initiatives that strengthen accountability, ownership and a high-performance culture. • Ensure company values are embedded throughout employee programs, performance evaluations and day-to-day operations. • Continuously identify opportunities to simplify processes, eliminate inefficiencies and improve the employee experience. • Support strategic people initiatives and organizational projects as the company grows.