Software Data Engineer - Machine Learning - Data Cloud
Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse big data sources to generate actionable insights and solutions for client services and product teracts with product and service teams to identify questions and issues for data analysis andexperiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. Job duties are varied and complex utilizing independent judgment. May have project lead role. 5 years relevant work experience.
BS/BA preferred. Oracle is an Affirmative Action-Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veterans status, age, or any other characteristic protected by law. Introducing the Oracle Data Cloud We are looking for a _Senior Software and Data Engineer
- Machine Learning_ for the Identity Graph Data Science team at Oracle Data Cloud (ODC), where we are leveraging the power of big data, cloud technologies, and data science to perform entity resolution across thousands of disparate data sources to create comprehensive and accurate anonymized profiles. Creating anonymized profiles at scale that link email, mobile, browser, tv, and postal address in a privacy safe and accurate manner is the foundation to any successful marketing campaign and the backbone of ODC s offerings. The Identity Graph is made possible because of massive data sets, high engineering standards, and advanced data science. As a Senior Data Scientist within the Identity Data Science (iDS) Research & Development team, you ll be involved in developing a best-in-class ID Graph that fuels the ODC. In this role, you will be doing a blend of traditional data science work and big data/software engineering. You will be building scalable, cost-conscious, stable, repeatable, and accurate machine learning and graph-based ETL pipelines in the cloud. This work may span all aspects of the data science and software development lifecycle. To be successful in this role, you must be equally an expert in machine learning and big data/software engineering. Role Develop and maintain production-scale ML systems, including ETL and modeling runtimes. Collaborate with other data scientists and engineers to design, research, and implement new data science products. Maintain and improve existing analytics solutions. Build tools to help team members and stakeholders interact with and understand our data science products. Bring an open mind and understanding of established engineering best-practices with regards to software lifecycle, code reviews, GI
T branching, and structuring complex ETL container-based build pipelines. Prerequisites A successful candidate must have experience with Spark programming.
BS / MS in Computer Science or equivalent industry experience that provided exposure to big data / ML and software engineering. 1 years experience working on large-scale data processing systems in production including data ingestion, normalization, and storage. Ability to apply core software engineering principles to practical business and machine learning problems. Fluency in Scala. Experience developing Spark applications at scale, including tuning and debugging. Experience with build pipelines (Jenkins) and software build tools (python packaging, sbt, gradle). Experience with monitoring production data workflows with all aspects of CI/CD. Experience with container-based architecture (Docker or comparable). Ability to automate the setup and management of data infrastructure in any cloud environment Nice-To-Haves Experience with Elastic
Search and Kibana. Fluency in Python Expert at writing complex SQL queries. Understanding of machine learning model evaluation techniques; ability to assess, diagnose, and reason about a model's performance. Understanding of the spatial interpretations of modeling features. Understanding of common machine learning models and when to apply them. Job: Business Operations Organization: Oracle Title: Software Data Engineer
- Machine Learning
- Data Cloud Location:
CO,Colorado-Broomfield Requisition ID: 20000JMX Other Locations: United States