By blending modern analytics capabilities with business strategy, you will help influence the core infrastructure and foundational technologies for Microsoft's online services including Bing, Office 365, Xbox, OneDrive, and the Microsoft Azure platform.

As a Data Scientist - Credit Risk (aka Credit Risk Analyst) you will have a hybrid work schedule, both remotely from your home office in the Dallas-Fort Worth area and on-site at our Administrative Office (HQ) in Irving (Las Colinas), Texas.

At Home Data entry or administrative assistant experience is not required but useful. Various payment methods, including PayPal, direct check, or online virtual gift card codes. With most of our paid researches, you have the alternative to take part online or in-person.

Intake Coordinator LVN/LPN Qualifications Requires a valid license as a Licensed Vocational Nurse or Registered Nurse Minimum of one year experience as an LVN or RN in a medical setting, preferably home health Knowledge of state and federal and accreditation requirements Data entry skills, excellent verbal and written communication skills (especially telephone.

Data integration experience with popular database, including SQL Server, Oracle, MySQL, Postgres SQL, Polybase, Cosmo DB, MongoDB, and others. Knowledge of OLTP, OLAP, tabular model, star schema, master data management, data governance, Azure Purview, DevOps, SDLC, Agile, statistics, data science, ML, MLOPS, and AI.

This is a remote work from home position perfect for those with any type of work background such as administrative assistant, data entry clerk, typing, customer service representative, drivers etc.

Experience with Alteryx (Designer/Server) or similar, DBT, and cloud-based storage/databases/data-warehouses (Redshift, Snowflake, etc.) Using tools like Alteryx, Tableau, DBT and platforms like Snowflake create innovative data solutions for media/marketing teams optimization processes.

This analytical data model should be the underpinning of all the reporting, dashboards, ad-hoc, Model Risk Management visualizations and statistics, etc. Design, develop, and deliver production-level, reusable, and scalable Natural Language Procession (NLP) architecture data pipeline solutions using Python and/or Scala programming languages.

Experience with Big Data Technologies such as AWS Redshift, RDS, S3, Glue, Athena, EMR, Spark and PySpark, Snowflake, Hive etc. Understanding of Data Models (e.g. Fact-Dimension), Data Topology (e.g. Star, Hub and Spoke) and ER (Entity Relationship) Diagrams.

Demonstrable experience working in transformational projects where you implemented data platforms and/or ETL/ELT/CDC pipelines using Databricks. Extensive hands-on experience implementing Lake house architecture using Data bricks Data Engineering platform, SQL Analytics, Delta Lake, and Unity Catalog.

Provide expert level business process guidance on data management functionalities within SAP including: BI (including BW, BODS, BAPI), ETL, Data Archiving, Data Migration, Data Conversion and Data Loads, Data Distribution, Data Maintenance, Data Governance, Data Analysis, Data Extracts and Reporting, Data Mapping, Data Validation, Data Reconciliation, and Data Refreshes and Upgrades.

7+ years’ experience hands-on implementing or managing daily operations of consumer data, digital marketing, digital analytics, ab testing, personalization, and/or BI solutions (for example Google Analytics (Universal Analytics and GA4), Tealium (IQ and AudienceStream CDP), ActionIQ/MetaRouter, Adobe Target/Analytics/Experience Platform/Launch, Google Marketing Platform, Rudderstack, Optimizely, Sitecore, Marketo/Salesforce Marketing Cloud/Eloqua, Microsoft CDP/PowerBI, Tableau.

Certified Information Systems Auditor (CISA), Certified Internal Auditor (CIA), Certified Public Accountant (CPA), Certified Fraud Examiner (CFE) and/or relevant data analytics certification preferred.

You will deliver technical solutions and address highly complex challenges and opportunities by driving cross-team coordination with the oversight of material management, IBP, Ariba, and Master Data Supply Chain & Financial Architecture.

You are paid within the salary range based on your experience and market data of the position. Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive.