• Applies moderately advanced mathematical, statistical, and quantitative techniques to solve medium-to-large scale business problems that significantly impact current and future business strategies. • Builds descriptive or explanatory models or uses the output of models created by others. • Analyzes larger datasets to identify trends, patterns, and business opportunities. Leverages interactive data visualization tools and statistical techniques such as distribution analysis, correlation analysis, outlier detection, multivariate analysis, time series, machine learning, and others to uncover hidden insights. • Conducts thorough exploratory data analysis (EDA) to uncover opportunities including testing hypotheses and validating findings with business partners. • Facilitates discussions with cross-functional business partners and teams to understand and collaborate on complex business objectives. • Influences solution strategies and outcomes by leveraging expanded knowledge of the business. • Collects data from a variety of sources and integrates and transforms disparate datasets to create cohesive datasets for analysis. • Assesses data quality and applies data hygiene techniques to ensure accuracy and consistency. • Supports data reliability by conducting quality checks, documenting data processes, and collaborating with more experienced analysts for peer review and data validation as needed. • Assists deployment and monitoring of more complex predictive models into workflows. • Translates technical data insights into communications and presentations for non-technical business partners and leadership to ensure data-driven insights and recommended action plans are easily understandable. • Actively seeks feedback from more experienced team members and engages in professional development opportunities to enhance skills and contribute effectively to team objectives.

Role Description The Data Analyst/ETL Developer plays a crucial role in providing insights for decision making. The Data Analyst transforms data into usable metrics through data processing software and business development strategies to provide valuable insights to company stakeholders. Job Roles and Responsibilities - Utilize SQL, and/or Python in data analytics to collect, understand, transform, cleanse, store, and share data in a privacy-preserving way. - Debug mappings and identify errors and error rows so that they can be corrected and re-loaded into a target system. - Review and analyze functional requirements and mapping documents. - Develop, maintain, and support ETL data pipelines for healthcare products and analytics platforms. - Initialize and configure data sites/environments to enable downstream analytics and reporting by partner teams. - Collaborate with upstream and downstream teams to ensure successful site onboarding, handoff, and readiness. - Monitor ETL jobs and pipelines in production, identifying failures, performance degradation, and data anomalies. - Troubleshoot and resolve production issues in ETL workflows, including failed loads, data mismatches, and processing delays. - Perform root cause analysis for pipeline incidents and implement corrective and preventive fixes. - Validate incoming healthcare datasets prior to release for downstream consumption. - Build and maintain data validations to ensure: - source to target reconciliation - row counts and completeness - business rule enforcement - data type, format, and constraint integrity Qualifications - Bachelor's degree in Computer Science, Data Analytics, Information Technology, Finance, or a related field. - 6 months to 1 year of experience with SQL and data analytics. - Proficiency in SQL for data manipulation, extraction, and analysis. - Strong analytical and problem-solving skills with the ability to interpret complex data sets. - A proactive problem solver with a keen attention to detail. - Familiarity with agile development methodologies and a collaborative mindset. - Excellent communication skills to effectively translate technical concepts to non-technical stakeholders. Requirements - The salary range for this position is $80-90k. Specific offers take into account a candidate’s education, experience and skills, as well as the candidate’s work location and internal equity. This position is also eligible for health insurance, 401k and bonus opportunity. Benefits - Medical, dental and vision coverage with low deductible & copay. - Life insurance. - Short and long-term disability. - Paid Parental Leave. - 401(k) + match. - Employee Stock Purchase Plan. - Generous Paid Time Off – accrued based on years of service. - 10 paid company holidays. - Tuition reimbursement. - Flexible Spending Account. - Employee Assistance Program. - Sick time benefits – for eligible employees, one hour of sick time for every 30 hours worked, up to a maximum accrual of 40 hours per calendar year, unless the laws of the state in which the employee is located provide for more generous sick time benefits. EEO Statement Claritev is an Equal Opportunity Employer and complies with all applicable laws and regulations. Qualified applicants will receive consideration for employment without regard to age, race, color, religion, gender, sexual orientation, gender identity, national origin, disability or protected veteran status. Application Deadline We will generally accept applications for at least 5 calendar days from the posting date or as long as the job remains posted.

• Gather and report meaningful metrics. • Maintain Quarterly dashboard development timelines and keep up with additional work requirements. • Validate and replace currently captured metrics with more meaningful metrics across operational teams on a regular, routine basis, at least bi-annually. • Ensure that as metrics, work products, and outputs mature and change over time, that definitions are updated on a routine basis from the Measures and Metrics (M&M) lexicon within current dashboard. • Incorporate additional available metric sources (Malware Next Generation (MNG), Customer engagement data from CISA public releases, and others). • Consolidate and align data sources to streamline the overall M&M data structure on a repeatable and routine basis to ensure that, as data sources change, the underlying framework remains efficient and trustworthy. • Consistently and regularly enhance our relational data model and compartmentalize datasets to strengthen governance, improve data capture, and ensure long-term scalability and maintainability. • Build and maintain predictive analytics and insights around current data holdings to enable decision making. • Build and maintain Performance Measure Definition Forms for metrics and measures currently captured. • Define how each measure is calculated, what fields are used, what systems they come from to ensure consistency and accuracy of measurement. • Integrate and establish repeatable workflows and data sharing with new Performance Management Working Group (PMWG). • Assist with standardizing and streamlining performance measurements across external organizations, to include performance measure development, tracking, reporting, and management.

• Own analytics-ready datasets and dashboards from requirements through delivery and adoption • Lead QA and UAT processes for new datasets, pipelines, and data products • Define acceptance criteria, test plans, and validation checks • Ensure data accuracy, completeness, usability, and consistency • Partner with data engineering to investigate root causes of data issues and bugs • Query and validate complex datasets using SQL and Python • Analyze large datasets to identify trends, patterns, and actionable insights • Partner with marketing and business teams to enable audience segmentation for acquisition, engagement, and retention initiatives • Act as the primary liaison between business stakeholders and technical teams