• Experience in writing complex SQL queries and experience with any data visualization tool is preferable e.g., Tableau, Power BI. • Good exposure of Software Testing methodologies, Implementation of Data Lakes, Data warehouse/ETL projects, Big Data projects in On-Premises & Cloud Environments. • Experienced in SAS applications and Python Programming. • Ability to write SQL queries to conduct data validations and probe quality issues with data. • Experience in Project Delivery Methodologies: SDLC, Iterative, Agile, Scrum, Kanban. • Experience in ALM Tools like JIRA, TFS (Azure Devops) & Confluence. • Knowledge on data quality fundamentals and data governance concepts. • Hands-on experience with all levels of testing includes Smoke Testing, Integration Testing, System Testing and Regression Testing. • Knowledge of PL-SQL, PySpark & SQL, on framing and tuning the Queries so that it covers all the data scenarios. • Accountable for high quality and on time delivery for task assigned. • Good knowledge in MS Office Tools. • Tracking all software versions, features, bugs and validation efforts for all software created and/or modified by the Development teams. • Developing and utilizing test data sets. • Creating and executing manual test scripts which includes testing software applications for quality and functionality using defined validation protocol and testing techniques. • Creating associated validation documentation using defined documentation methods. • Working with application developers in resolving issues and retesting applications. • Good verbal and written communication. • Actively participates in the testing of new Clario products by: Developing test cases and study data Conducting testing for general testing Conducting testing for Clinical Services development tools Reporting testing and review anomalies, as appropriate, to the department head. • Actively participates in post-production product release testing by: Developing test cases Conducting regression and bug fix testing for Clinical Services. Report testing and review anomalies. • Secondary Responsibilities: Exploring new opportunities to add value to organization and departmental processes. Attending and participating in applicable company-sponsored training Reading, understanding, and adhering to organizational Standard Operating Procedures (SOPs) Establishing and enforcing departmental standards Exploring new opportunities to add value to organization and departmental processes. Helping others to accomplish results. Performing other duties as assigned. Attending and participating in applicable company sponsored training. Attending educational workshops and reviewing professional publications. Benchmarking state-of-the-art practices. Participating in professional societies. Keeping informed of changes in the regulatory environment and/or regulatory requirements.

• Develop new methods that provide clinically actionable results from sequencing data; • Create and optimize bioinformatics pipelines, balancing biological answer quality with computational performance; • Ensure reproducibility and traceability of analyses, guaranteeing that clinical processing is consistent and auditable; • Perform ad hoc analyses of experimental laboratory data to inform decisions about standardizing new pipelines; • Work in a multidisciplinary team, writing clean, maintainable code with good test coverage; • Understand key sequencing metrics and automate quality-control checks.

• Support global compensation programs and cycles • Conduct compensation analysis and pay equity reviews • Prepare reports for annual planning and decision-making • Ensure data integrity and compliance with policies

• Design, develop, and optimize fraud strategies across personal loans and student loan refinance products • Monitor portfolio performance to identify emerging fraud trends, risks, and optimization opportunities • Develop and deploy fraud rules and strategies using segmentation, statistical analysis, and predictive modeling techniques • Own end-to-end fraud mitigation processes, with accountability for fraud loss reduction and performance outcomes • Design and execute A/B tests and champion/challenger frameworks to evaluate strategy effectiveness • Build and maintain scalable analytical frameworks using tools such as Snowflake and dbt • Develop dashboards and reporting (e.g., Looker) to monitor KPIs such as fraud rate, approval rate, and false positives • Generate actionable insights from structured and unstructured datasets, including limited or noisy data environments • Partner with cross-functional teams (Product, Engineering, Risk, Operations) and external vendors to implement fraud solutions • Leverage internal and third-party data to enhance fraud detection capabilities • Continuously evaluate and refine strategies based on performance metrics and evolving fraud patterns • Communicate insights, strategy performance, and model behavior clearly to stakeholders and senior leadership • Support model development lifecycle, including design, validation, and production deployment