Role Description You will be joining our Data & Automation Services team, a unit that sits at the intersection of data at scale and manual workflows requiring domain knowledge. The role spans two complementary tracks: - Conferences, where you will own the scraping pipeline and the run-rate of upcoming conference coverage. - Cross-vertical automation and data work for the wider business, ranging from ad hoc data extraction to one-off projects. For this, you will: - Maintain an active run-rate of upcoming conferences and continuously grow conference coverage on the platform. - Perform end-to-end delivery of one-off projects and recurring automation workflows. - Investigate and identify potential trade fairs and assess the value of scraping their exhibitor lists as well as researching additional data points. - Set up and run web scrapers using tools like Octoparse and Firecrawl to extract exhibitor lists and relevant information for projects. - Regularly update and maintain the content management system to ensure the information remains up-to-date and accurate. - Report and communicate problems and come up with solutions that will be integrated into a worldwide feature. - Communicate with internal stakeholders in a guided manner to define project requirements for cross-vertical work. - Support ad hoc data extraction and reporting requests from the wider business, working from a read-only dataset (e.g. monthly reporting, data completeness and accuracy reports). - Contribute to one-off AI-driven data gathering projects (e.g. extracting HQ locations for investors, advisors and lenders, or pulling financial information from annual reports). - Support internal tech-forward initiatives, such as Slack and Notion integrations that streamline analyst workflows. As this is a newly-shaped team and process, there is ample opportunity for you to refine and improve how we work — and to grow alongside it! Qualifications - Experience – You have a finished University degree and have experience with Python, scraping, and database management. - Education – You have consistently achieved excellent results from a leading university in a computer science, data science or related field. - Workplace enthusiasm – You showcase a strong interest in project management, database management and data management techniques and possess strong attention to detail. - Languages – You are fluent and articulate in English. Benefits - High-growth fintech scale-up with an international footprint. - Competitive compensation package. - Unmatched learning and career preparation opportunities for private equity, investment banking or consulting. - Clear development path supported by lots of coaching and a feedback-driven approach. - Flexibility to work remotely and leeway around exam periods or deadlines. - Fun working atmosphere with company-wide outings and events. - Culture of trust, ownership and standard of excellence.

Role Description The Supervisor, Encounter Data Management develops business processes to ensure successful submission and reconciliation of encounter submissions to Medicaid/Medicare. Responsibilities include: - Ensuring encounter submissions meet or exceed all compliance standards via analysis of data. - Developing tools to enhance the encounter acceptance rate by Medicaid/Medicare. - Looking for long-term improvements of encounter submission processes. - Making decisions related to schedule, plans, and daily operations. - Performing escalated or more complex work of a similar nature. - Supervising a group of typically support and technical associates. - Coordinating and providing day-to-day oversight to associates. - Ensuring consistency in execution across the team. - Holding team members accountable for following established policies. - Ensuring data integrity for claims errors. - Collaborating with management and top professionals/specialists in the selection of methods, techniques, and approaches. You will report to the Manager, Encounter Data Management. Qualifications - 2+ years Medicare and/or Medicaid claims processing experience. - Internal and external error claim processing. - 2+ years of formal or informal leadership experience. - 1+ years' experience working in CAS, Edifecs, Optum, and similar DOS 835/837 warehouse systems. - 2 years+ of advanced Microsoft Excel (VLOOKUP, Pivot Tables, and ability to create macros). - 1 year+ SQL experience (running queries). Requirements - Demonstrated ability to give direction. - Proven ability to collaborate with multiple departments. - Ability to deliver presentations to senior leadership. Benefits - Medical, dental, and vision benefits. - 401(k) retirement savings plan. - Time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave). - Short-term and long-term disability. - Life insurance. - Many other opportunities. Additional Information - Work-At-Home Requirements: Must have the ability to provide a high-speed DSL or cable modem for a home office. - A minimum standard speed for optimal performance of 25x10 (25mbps download x 10mbps upload) is required. - Satellite and Wireless Internet service is NOT allowed for this role. - A dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information. - Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. - Scheduled Weekly Hours: 40. - Pay Range: $65,000 - $88,600 per year, eligible for a bonus incentive plan based on company and/or individual performance.

Role Description This position works out of our Kansas City, Lake Forest, Willis Tower, or remote locations near an Abbott office in the eScreen Business Group in Abbott Rapid Diagnostics. We’re empowering smarter medical and economic decision-making to help transform the way people manage their health at all stages of life. Every day, more than 10 million tests are run on Abbott’s diagnostics instruments, providing lab results for millions of people. The AI / BI Engineer contributes to the design, development, and operation of analytics and AI‑ready data solutions on Azure. This role focuses on building reliable data pipelines, Lakehouse and Lakebase Postgres assets, and AI‑enabled applications under the guidance of senior and lead engineers, while developing deep expertise in Azure Databricks, BI, and AI foundations. This is an individual contributor role for someone that is ready to grow their skills in Abbott; we do not expect you to be an expert at this level. What You’ll Work On - Data & Lakehouse Engineering - Develop and maintain batch and streaming pipelines using Azure Databricks, PySpark, and SQL. - Contribute to Lakehouse and Medallion Architecture components supporting BI, AI, and operational workloads. - Assist in designing and maintaining Lakebase Postgres data models to support AI applications and agents. - Build curated datasets and semantic layers for Databricks AI/BI Dashboards, Genie Spaces, Power BI, and downstream consumers. - AI Platform & Application Support - Support Lakebase Postgres‑powered AI applications, ensuring data accuracy and reliability. - Contribute to Databricks Apps that surface analytics and AI insights to business users. - Assist with development and enhancement of AI agents, including data preparation and embedding pipelines. - Support ML workflows using MLflow and Azure ML integrations. - Contribute to generative AI pipelines such as embeddings, vectorized data, and RAG workflows. - Platform Operations & Collaboration - Monitor and troubleshoot pipelines and application workloads. - Follow established Unity Catalog, governance, and security standards. - Collaborate with BI developers, data scientists, and senior engineers to deliver business outcomes. Qualifications - Bachelor's degree in STEM related field or associate's degree in similar field and 7 years of experience in similar area. - 3 or more years of experience in similar area of expertise with bachelor's degree. Requirements - Preferred: Databricks Certified Generative AI Engineer Associate. - Azure: Familiarity with ADLS Gen2, Synapse/Data Factory, Key Vault, and cloud fundamentals. - AI & ML: Understanding of ML and generative AI concepts. - Programming: Proficiency in Python and SQL; exposure to PySpark preferred. - Databricks Platform: Working knowledge of Spark, Delta Lake, and Databricks Apps. - Lakebase Postgres & AI Foundations: Introductory experience with relational modeling and AI data access patterns. - Preferred: Databricks Certified Generative AI Engineer Associate. - Azure: Familiarity with ADLS Gen2, Synapse/Data Factory, Key Vault, and cloud fundamentals. - AI & ML: Understanding of ML and generative AI concepts. - Master's Degree in similar field. Benefits - Career development with an international company where you can grow the career you dream of. - Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year. - An excellent retirement savings plan with a high employer contribution. - Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree. - A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune. - A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists.

• Design, build, and deploy AI-enabled applications that support real operational workflows and decision-making for DoW, federal, and enterprise environments. • Develop application logic that integrates AI models, APIs, data pipelines, user interfaces, and enterprise systems. • Implement retrieval-augmented generation, semantic search, embeddings, vector databases, prompt strategies, and agent-based workflows where appropriate. • Integrate structured and unstructured enterprise data sources into AI-enabled applications. • Build orchestration workflows that connect foundation models, machine learning services, tools, APIs, and secure enterprise environments. • Develop evaluation frameworks to measure AI output quality, grounding, accuracy, traceability, and failure modes. • Implement guardrails, validation checks, fallback logic, and human-in-the-loop review points to support reliable AI behavior. • Support training, tuning, evaluation, and validation of AI or machine learning models using enterprise data while ensuring outputs remain defensible, explainable, and aligned to approved methodologies. • Develop secure APIs, backend services, dashboards, visualizations, and integration components for AI-enabled analytic tools and decision-support platforms. • Implement monitoring, logging, observability, model performance tracking, and cost controls for AI systems in operation. • Advise on model transparency, explainability, auditability, data governance, information assurance, and access controls required for secure DoW and federal deployment. • Collaborate with functional SMEs to translate business needs, mission requirements, workflow requirements, review expectations, and operational constraints into technical requirements. • Contribute reusable AI components, accelerators, reference architectures, and delivery patterns for future enterprise and federal AI implementations. • Support demonstrations, pilots, proofs of value, testing, deployment readiness, and user acceptance activities with internal and client stakeholders.