• Own the end-to-end data architecture for the Data Warehouse Foundation, designing for AI-first consumption across GPT assistants, AI agents, predictive models, and operational intelligence — in addition to BI and reporting. • Lead data modeling across all 11 departments, designing canonical enterprise data models that serve cross-functional AI and analytics use cases without duplication or fragmentation. • Design and implement the contextual intelligence layer — including RAG architecture, vector store strategy, knowledge base ingestion pipelines, and document and unstructured data processing — that powers Agiloft's enterprise knowledge system. • Build and maintain the agentic data integration layer: real-time and near-real-time data access patterns, agent memory and state persistence design, orchestration data requirements, and agent output integration back into the warehouse. • Own the AI/ML feature layer — feature engineering strategy and standards, training data pipeline design, feature store architecture, and model output integration — enabling predictive analytics across churn, pipeline health, and operational forecasting. • Design and govern the operational data and GPT context layer, including structured context feed design for GPT assistants, data freshness and access SLAs for AI use cases, and cross-departmental data reuse standards. • Lead the Data Warehouse Foundation build in partnership with the external consulting team — setting architecture standards, reviewing implementation against AI-first principles, and ensuring the five-wave build plan delivers a foundation that serves the full intelligence architecture. • Design and manage data ingestion, ELT/ETL, and orchestration pipelines across all source systems, ensuring reliability, performance, and cost efficiency. • Establish and enforce AI data engineering standards across the organization — prompt-adjacent data design, agent data access patterns, reusable pipeline components, and quality assurance processes. • Own data access policy design and least-privilege access controls in partnership with Security, ensuring data made available to AI systems is governed, auditable, and compliant. • Define data quality standards and monitoring processes for AI-consumed data, where quality failures have direct impact on model and agent performance. • Partner with the Principal Data and Integrations Architect on infrastructure design, ensuring data modeling and AI consumption requirements are incorporated into pipeline and architecture decisions from the start — not retrofitted after build. • Partner with the VP FP&A and Manager of BI & Data to ensure the semantic and metrics layers are technically sound and serve both AI use cases and reporting requirements. • Manage the AI Ops data architecture roadmap, translating business and AI use case requirements from all 11 departments into sequenced, prioritized technical work. • Maintain documentation and knowledge transfer standards for all data architecture, pipelines, and integration patterns — ensuring AI Ops-built infrastructure is reusable, auditable, and not dependent on any single individual. • Collaborate with the AI Agent Engineer and GPT & AI Systems Lead to ensure data infrastructure supports agent orchestration, retrieval-augmented generation, and multi-step reasoning workflows. • Define the roadmap for data science and AI data work in partnership with the VP of AI Operations — this role does not take direction from IT on resource allocation or prioritization. All roadmapping is managed within AI Operations. • Evaluate and recommend data tooling, frameworks, and platform components in alignment with AI Ops' technology-agnostic, build-for-leverage approach. • Other duties as assigned.

Role Description Join MedPOINT Management as an Outpatient Data Entry Clerk, where you will play a crucial role in maintaining accurate patient records and supporting our healthcare team. This is an exciting opportunity to contribute to a company dedicated to improving patient care through efficient data management. Responsibilities: - Accurately enter and maintain patient data in the electronic health record system. - Verify and update existing patient information to ensure data integrity. - Assist in the preparation of reports and data summaries for clinical staff. - Respond to data inquiries from healthcare professionals and administrative staff. - Collaborate with team members to optimize data entry processes. - Ensure compliance with HIPAA regulations and data security protocols. - Participate in training sessions to enhance data management skills. - Support additional administrative tasks as needed to ensure smooth operations. Qualifications - High school diploma or equivalent; associate degree preferred. - Proven experience in data entry or administrative support, preferably in healthcare. - Strong attention to detail and accuracy in data handling. - Proficient in Microsoft Office Suite and electronic health record systems. - Excellent organizational and time-management skills. - Ability to work independently and as part of a team. - Strong communication skills, both written and verbal. - Commitment to maintaining patient confidentiality and data security. Requirements - High school diploma or equivalent; associate degree preferred. - Proven experience in data entry or administrative support, preferably in healthcare. - Strong attention to detail and accuracy in data handling. - Proficient in Microsoft Office Suite and electronic health record systems. - Excellent organizational and time-management skills. - Ability to work independently and as part of a team. - Strong communication skills, both written and verbal. - Commitment to maintaining patient confidentiality and data security. Benefits - 401(k) - 401(k) matching - Dental insurance - Employee discounts - Free food & snacks - Health insurance - Opportunity for advancement - Paid time off - Parental leave - Savings bank - Training & development - Vision insurance - Wellness resources

At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers' evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection. Job Description Founded by The Allstate Corporation in 2016, Arity is a fully remote data and analytics company focused on improving transportation. We collect and analyze enormous amounts of data, using predictive analytics to build solutions with a single goal in mind: to make transportation smarter, safer and more useful for everyone. At the heart of that mission are the people that work here-the dreamers, doers, and difference-makers that call this place home. As part of that team, your work will showcase both your intelligence and your creativity as you tackle real problems and put your talents toward transforming transportation. That's because at Arity, we believe work and life shouldn't be at odds with one another. After all, we know that your unique qualities give you a unique perspective. We don't just want you to see yourself here. We want you to be yourself here. Arity Analytics Data Platform Arity's Analytics Data Platform (ADP) team enables our analytics and data science teams to research, develop, deploy, and optimize analytics products that drive Arity's mission forward. The ADP team defines, provisions, and manages data pipelines, tools, platforms, and infrastructure to optimize analytics workflows and facilitate efficient collaboration with Arity's engineering teams to bring analytics products to production. We promote best practices for code and model management, reproducibility, scalability, and governance of the end-to-end analytics lifecycle. The team also plays a central role in the adoption and effective use of emerging AI-based development tools within the Arity Analytics community. The Role: You will lead a team of data and infrastructure engineers in the overall delivery of data solutions enabling advanced data science and analytics. This includes the development and management of cloud-based big data systems for ingesting, processing, and managing spatial-temporal and other types of data for analytics R&D; the implementation and operationalization of advanced data processing pipelines and AI solutions; identifying and integrating new data management and data analytics tools and ensuring best practices in their usage; and establishing and administering MLOps best practices in collaboration with Arity Engineering. The Senior Manager is responsible for the recruitment, selection, mentorship, and development of team members and for setting the strategic direction for the team in support of the business objectives of the company. This role is also accountable for building alignment with key stakeholders across Arity on the big data management strategy and execution. Key Responsibilities: - Manage and develop the Analytics Data Platform team and drive technical excellence. - Drive the analysis, design, and development of a roadmap and implementation plan to continuously modernize our analytics data and model management platform and improve operational efficiency in accordance with business objectives. - Implement data security measures and ensure compliance with data governance policies and standards. Engineer secure app patterns into cloud platforms. - Use your knowledge of cloud design patterns, cloud operations, and cloud cost models to identify and address performance bottlenecks, troubleshoot technical issues, and implement optimizations to enhance overall data & model management platform performance. - Be a subject matter expert in cloud computing & model management/MLOps to help data scientists and analysts work effectively in the cloud environment. - Work collaboratively with cross-functional teams, including data scientists, analysts, engineers, and business stakeholders, to understand data and ML system requirements and deliver effective solutions. - Be a technology thought leader and a key influencer on technical decisions and organizational strategy that have long-term, strategic impact on the business. Functional Skills: - Deep knowledge about public cloud architecture, cloud strategy, cloud operations, compliance, and related tools. - Hands-on experience in designing and delivering big data management and applications on cloud platforms using modern software development processes, methodologies, and tools. - Demonstrated experience in working with cloud-based ML frameworks, such as AWS Sagemaker AI, Google Vertex AI, Microsoft Azure ML, or Databricks, and in MLOps workflows, patterns and delivery objectives. - Proficient in system design or a programming language such GoLang, Scala, Python - Demonstrated experience in designing and supporting cloud-based data lakes/warehouses/lakehouses - Excellent collaboration skills and ability to work on a remote team. - Strong analytical, problem solving, and organizational skills. Experience: - 10 or more years of experience (preferred) Supervisory Responsibilities: - This job has supervisory duties. #LI-TE1 Skills Amazon S3, Amazon SageMaker, Amazon Web Services (AWS), Data Science, Google BigQuery, Google Cloud Platform (GCP), Machine Learning Operations, Vertex AI Compensation Compensation offered for this role is 151,700.00 - 221,675.00 annually and is based on experience and qualifications. The candidate(s) offered this position will be required to submit to a background investigation. Joining our team isn't just a job - it's an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger - a winning team making a meaningful impact. Allstate generally does not sponsor individuals for employment-based visas for this position. Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component. For jobs in San Francisco, please click "here" for information regarding the San Francisco Fair Chance Ordinance. For jobs in Los Angeles, please click "here" for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance. To view the "EEO Know Your Rights" poster click "here". This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs. To view the FMLA poster, click "here". This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint. It is the Company's policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee's ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.

• Design, build, and operate highly scalable, low latency data platforms • Create modern data lakehouse architectures, real time data pipelines, and analytics ready data models that support trading, risk, reporting, and regulatory requirements • Collaborate closely with trading desks, product teams, AI/analytics teams, and architects to deliver reliable, secure, and high performance data solutions