• Pull, clean, normalize, and analyze large and complex datasets from internal Lilly systems (such as transactional, claims, distribution, and pricing data) and external sources in support of investigations. • Work collaboratively with lawyers, investigators, forensic laboratory analysts, and intelligence professionals to initiate, advance, and conclude investigations. • Identify data anomalies, irregular patterns, and statistically significant trends that may indicate fraud, diversion, counterfeiting, or other legal violations. • Validate data to evidentiary standards, for use in litigation or referrals to law enforcement, and appropriately qualify uncertainty in analysis. • Develop and maintain data pipelines, dashboards, and automated monitoring tools to proactively surface high-value investigative leads. • Prepare clear, well-documented analytical reports, visualizations, and data summaries that support investigative strategy and enforcement actions. • Work with Legal and compliance partners to advise on data-driven risk mitigation, controls improvements, and fraud prevention measures. • Consolidate and integrate data across Lilly systems and help manage access and data governance in support of SIU operations. • Perform detailed documentation of analytical methods and findings within the SIU’s internal case management system. • Partner with outside counsel, experts such as forensic accountants, and law enforcement on investigations and any resulting civil or criminal actions. • Throughout all assignments and investigations, maintain company confidential information, use discretion in conducting sensitive investigations, comply with all national and local laws, and preserve all applicable privileges.

Overview This is a remote role that may be hired in several markets across the United States. Perform duties as a subject matter expert for data delivery across multiple data domains per the business units data needs. Collaborate with large cross-functional teams, SMEs, vendors, etc. to deliver governed data. Act as a data SME and partner with diverse group of business functions to define requirements, analysis, mapping, validation and resolve any data issues. Perform detailed data analysis to translate business requirements into source to target data mappings for CDEs (Critical Data elements). Create and maintain all relevant documentation for Enterprise data warehouse which includes source-to-target mappings, data dictionaries, and other related materials. Communicate and guide technology teams through data mapping documents in implementing the solutions. Identify areas of improvement in current data infrastructure and work with key stakeholders to fix them. Validate functional workflow, business rules, and formulae through data profiling using SQL (Structured Query Language) queries. Work closely with business stakeholders to share insights and data issues. Perform ad-hoc analytics using advanced SQL to extract business value and answer questions from stakeholders. Drive and enforce data governance framework to ensure high quality strategic data solutions. Develop and execute procedures and processes to certify data quality for business purposes. Ensure data consistency, accuracy, timeliness, validity, and completeness. Represent data management group in various forums such as Internal / external audits, status updates, and respond to queries in an effective and timely manner. This is a remote role that may be hired in several markets across the United States. Qualifications Position requires a Bachelor’s degree in Information Technology, or a related field plus six (6) years of experience in the job offered or six (6) years of experience as Data Management, Project Manager, Data Analyst or related occupation. Requires 5 years of experience in banking and financial services. Requires expert proficiency in working with SQL. Requires deep understanding of Data Warehousing and transformation methods, and ETL processes. Requires proven experience in Data Management, Data Analysis, Data Quality, Data Governance, Metadata management, lineage documentation, Data Profiling, Data Mapping and Data Validation. Requires knowledge of data spreadsheets and databases, Business Analytics, and Alteryx. Requires knowledge of data governance best practices and tools (such as Collibra). Requires hands on experience in ETL tools for building data pipelines and process automation. Requires relevant experience in BI reporting tools, both Tableau and Business Objects. Requires experience supporting monthly close process and ad-hoc projects as needed. This is a remote role that may be hired in several markets across the United States. The base pay for this position is generally between $164,000 to $191,496 per year. Actual starting base pay will be determined based on skills, experience, location, and other non-discriminatory factors permitted by law. For some roles, total compensation may also include variable incentives, bonuses, benefits, and/or other awards as outlined in the offer of employment. Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits This job posting is expected to remain active for 31 days from the initial posting date listed above. If it is necessary to extend this deadline, the posting will remain active as appropriate. Job postings may come down early due to business need or a high volume of applicants. #EJC and #LI-DNI

About YSI Yellow Social Interactive is a dynamic and innovative leader in the social gaming industry, dedicated to creating engaging and interactive experiences across various platforms. Our commitment to excellence and creativity sets us apart in the market. We seek exceptional, talented individuals who aim for excellence. With offices in Gibraltar, Antigua, and bases in Malta and the Philippines, plus a global remote team, we welcome motivated people capable of building and scaling business functions. Job Purpose As Rewards Data Analyst, you will be responsible for ensuring that incentives, rewards, and promotional spend are commercially effective, sustainable, and well controlled. The role focuses on analysing promotional performance, supporting data-driven offer design, and ensuring that incentive strategies maximise commercial impact while managing cost exposure and risk. Areas of Responsibility - Analyse the performance of incentives, rewards, and promotional campaigns to evaluate effectiveness and commercial return. - Monitor ROI, promotional spend, and cost exposure, ensuring offers support key commercial KPIs. - Identify and mitigate abuse risks, bonus leakage, and other inefficiencies in promotional activity. - Support offer design and pricing strategies through commercial modelling and performance analysis. - Provide clear insights and recommendations to VIP and Promotions Managers to help plan, optimise, and monitor promotional strategies. - Work closely with the Data Analytics team to develop and improve tools that support performance monitoring and cost control. - Collaborate with the Finance team to understand how marketing KPIs translate into financial performance and identify opportunities to optimise promotional impact. - Produce regular performance reports and actionable insights to support decision-making. Requirements - Bachelor’s Degree required (Marketing or Data Science an advantage). - 2+ years’ experience in a commercial role within the gaming industry. - Highly organised and proactive, with strong attention to detail. - Ability to work independently and meet tight deadlines. - Data-driven with strong commercial awareness. - Strong prioritisation skills and an enthusiastic “can do” attitude. - Excellent communication and collaboration skills.

Industry Technical / Data Infrastructure Work Arrangement Remote Job Type Full-time Work Schedule Standard business hours with required overlap with US Pacific Time (PST) Locations: - LATAM: Mexico City (Mexico), Bogotá (Colombia), São Paulo (Brazil), Buenos Aires (Argentina), Caracas (Venezuela), Honduras (Dominican Republic) - Anywhere in LATAM About Pearl Talent Pearl works with the top 1% of candidates from around the world and connects them with the best startups in the US and EU. Our clients have raised over $5B in aggregate and are backed by companies like OpenAI, a16z, and Founders Fund. They’re looking for the sharpest, hungriest candidates who they can consistently promote and work with over many years. Candidates we’ve hired have been flown out to the US and EU to work with their clients, and even promoted to roles that match folks onshore in the US. Hear why we exist, what we believe in, and who we’re building for: WATCH HERE Why Work with Us? At Pearl, we’re not just another recruiting firm—we connect you with exceptional opportunities to work alongside visionary US and EU founders. Our focus is on placing you in roles where you can grow, be challenged, and build long-term, meaningful careers. About the Company Our client is a technology-driven company operating at the intersection of data, infrastructure, and machine learning. They build large-scale datasets that power advanced analytics and AI systems, helping organizations make better decisions using real-world visual and geospatial information. The company operates in a fast-paced, high-ownership environment where data quality and execution excellence are critical to customer success. Role Overview The Infrastructure Analyst is responsible for analyzing roadway video and imagery to identify, classify, and document infrastructure conditions — including pavement distresses (cracks, potholes, rutting, raveling), road assets (signage, markings, barriers), and surface conditions. This role ensures accurate, consistent data delivery at scale. This is an ideal role for civil engineering graduates who want to apply their technical knowledge of pavements, road construction, and infrastructure assessment in a technology-forward environment. You will define standards, resolve ambiguous edge cases, and act as the final quality authority for datasets. The role works cross-functionally with Machine Learning and Customer Success teams while leading operational annotation teams. The ideal candidate is decisive, detail-oriented, and thrives in environments where speed, accuracy, and technical judgment must be carefully balanced. Your Impact - Deliver high-quality, customer-ready roadway condition datasets that directly support machine learning performance and infrastructure decision-making - Apply civil engineering knowledge to accurately identify and classify pavement distresses and road defects - Reduce ambiguity and improve data consistency across large-scale infrastructure assessments - Help scale data operations while maintaining strict quality standards - Enable faster iteration on ML models and stronger customer satisfaction through accurate ground-truth data Core Responsibilities Roadway Analysis & Data Creation – 40% - Analyze roadway video and imagery to identify pavement distresses: cracking (alligator, longitudinal, transverse, block), potholes, rutting, raveling, patching, and other surface defects - Classify infrastructure assets including signage, road markings, guardrails, drainage features, and barriers - Apply pavement condition assessment methodologies to ensure consistent, accurate classification - Own the full data creation lifecycle from video preprocessing through tagging, QA, and final delivery Quality & Standards – 25% - Define, document, and continuously refine classification standards for roadway conditions and assets - Build and maintain QA frameworks that ensure repeatable, high-quality output - Act as the final decision-maker on ambiguous classifications and edge cases - Identify recurring quality issues and implement corrective processes Team Leadership – 20% - Lead and manage annotation and review teams to meet quality and delivery targets - Train team members on pavement distress identification and classification standards - Set performance benchmarks and provide clear feedback to maintain consistency - Scale output while preserving quality standards Cross-Functional Collaboration – 10% - Partner closely with Machine Learning teams to align datasets with real-world infrastructure requirements - Work with Customer Success teams to ensure timely and accurate dataset delivery - Translate customer needs (transportation agencies, municipalities) into clear internal execution standards Process Improvement – 5% - Identify opportunities to automate or streamline tagging, QA, and review workflows - Build systems and processes that support growing dataset volume and complexity