Wix

• Assist TSD with data products by providing highly skilled and authoritative expertise on data engineering methods and best practices, including code-first development approaches and modern pipeline design patterns. • Design, implement, and maintain an efficient, secure, stable, and flexible data architecture that supports products and end-users, with all assets managed via source control. • Design, implement, and maintain ELT/ETL pipelines for efficient processing of source data in Azure Synapse and Azure Machine Learning (using SDK V1 and SDK V2) • Review, maintain, and improve existing architecture and pipelines, including periodic audits to address bottlenecks, deprecated dependencies, and architecture drift. • Establish quality controls for maintaining all pipelines, and introduce error handling, logging mechanisms, and validation checks. • Incorporate source control for all pipelines and data analytics codebases to enable iterative code development while ensuring data architecture stability. • Optimize the ingestion, processing, and storage of a wide variety of datasets and data types, including modern columnar formats such as Parquet. • Develop self-service capabilities for SBA OIG analysts to query and export data for investigations and audits. • Coordinate with data scientists to ensure the architecture efficiently supports machine learning algorithms and data pipelines in Azure Machine Learning. • Develop robust standard operating protocols (SOPs) dictating the authoring, development, validation, publishing, execution, and monitoring of all data pipelines and assets in Azure environment. • Provide detailed documentation of the data architecture, including data dictionaries, ER diagrams, and pipeline process maps. • Maintain and expand the environment with additional datasets and services upon request, following a defined intake and testing process prior to production deployment. • Stay current with emerging AI tools relevant to data engineering and contribute to exploratory efforts evaluating automation and LLM-assisted capabilities.

• Assist TSD with data analytic products by providing highly skilled and authoritative expertise on analytic methods. • Perform data quality analysis on source tables to identify any abnormalities or inconsistencies. • Review, maintain, and provide support using all existing fraud indicators developed by TSD. • Develop and refine repeatable processes for efficiently combining and analyzing large data sources (including relational tables, structured and unstructured datasets). • Collaborate closely with criminal investigators to determine and execute strategies to support cases; proactively address and communicate potential data quality issues and adapt analysis to shifting case needs; adhere closely to federal rules of criminal procedure governing protected information (e.g., Rule 6(e)). • Design, develop, and implement advanced statistical and machine learning models targeted at identifying fraud, improper payments, or non-compliance within SBA programs. • Utilize indicators of potential fraud, improper payments, or non-compliance to develop and test predictive models. • Assist in developing case leads for SBA OIG investigations based on model outcomes. • Coordinate with the Data Engineering Team to ensure system architecture is designed to efficiently support machine learning models. • Integrate and scale natural language processing methods to parse, clean, and analyze large corpora of unstructured or semi-structured text data, utilizing OCR, semantic similarity algorithms, and large language models as needed. • Provide detailed documentation of all methodology, test models, and production models; maintain records in compliance with criminal evidentiary requirements. • Develop visualizations and dashboards to demonstrate methodological choices, outcomes, and predictive capabilities of machine learning models; iteratively solicit and integrate end-user feedback. • Provide outcomes and recommendations in multiple formats, including data summaries and visualizations for investigative staff, and executive summaries for SBA OIG leadership. • Create programming and automation techniques to improve task efficiency using tools such as SharePoint, Python, Microsoft Excel, Power BI, and others. • Identify new business questions to expand the scope of analysis and reporting.

• Initiate outbound calls, emails, and messages to potential clients. • Respond promptly to inbound inquiries and guide clients through initial questions. • Engage in conversations to uncover client needs and goals. • Clearly explain service offerings and recommend next steps. • Schedule follow-up calls or connect clients with the right team members. • Log interactions and maintain accurate notes in our CRM.

• Initiate outbound calls, emails, and messages to potential clients. • Respond promptly to inbound inquiries and guide clients through initial questions. • Engage in conversations to uncover client needs and goals. • Clearly explain service offerings and recommend next steps. • Schedule follow-up calls or connect clients with the right team members. • Log interactions and maintain accurate notes in our CRM.

• Initiate conversations with potential clients and respond to inbound inquiries. • Understand each client’s unique goals, challenges, and decision-making process. • Recommend tailored financial solutions based on client input and available data. • Guide clients through onboarding, product selection, and service implementation. • Maintain regular contact with clients to support retention and satisfaction. • Communicate insights and client feedback to internal teams to help improve offerings.

• Identify potential clients and assess their goals, challenges, and needs. • Build lasting partnerships with decision-makers and key stakeholders. • Stay current on trends, tools, and developments that may impact client strategies. • Communicate with clients via phone, email, video calls, and other professional platforms. • Recommend personalized financial solutions and services based on client needs. • Act as a trusted resource by providing a seamless onboarding process and ongoing support. • Collaborate with internal teams to continuously improve client experience.

• Engage with new and prospective clients through outreach and follow-ups. • Understand each client’s financial goals and decision-making process. • Recommend solutions that align with their needs. • Guide clients through onboarding and product implementation. • Maintain accurate records in CRM tools. • Support clients with regular check-ins and ongoing service.

• Initiate outbound calls and respond to inbound client inquiries. • Conduct needs assessments to understand personal or business objectives. • Recommend appropriate services and walk clients through the onboarding process. • Manage follow-up outreach and relationship-building activities. • Maintain accurate CRM records and activity logs.

• Initiate outbound calls, emails, and messages to potential clients • Respond promptly to inbound inquiries and guide clients through initial questions • Engage in conversations to uncover client needs and goals • Clearly explain service offerings and recommend next steps • Schedule follow-up calls or connect clients with the right team members • Log interactions and maintain accurate notes in our CRM

• Connect with individuals exploring financial services. • Guide clients through the discovery process. • Recommend tailored solutions that support their personal or business goals. • Engage with new leads through calls, emails, and digital platforms. • Educate clients on next steps and facilitate a seamless onboarding process. • Track all outreach activity and manage follow-up communication in CRM. • Build long-term client rapport and ensure satisfaction.