Data Scientist (Energy)

Microsoft • Redmond, WA

2d

About The Position

Architect and Develop Data Pipelines: Design, build, and maintain scalable data pipelines and workflows using Python and SQL to support data integration, transformation, and loading processes. Build and Maintain ADO Pipelines: Develop and manage Azure DevOps (ADO) pipelines and other Azure Infrastructure (subscription, blob storage, VMs, etc.) to automate deployment and integration workflows, ensuring efficient and reliable delivery of data solutions. Implement Best Software Practices: Drive and enforce best practices in software development, including code reviews, testing, and continuous integration/continuous deployment (CI/CD) processes. Data Quality and Governance: Ensure data quality, integrity, and governance by implementing robust data validation, monitoring, and auditing processes. Collaborate with Cross-Functional Teams: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs. These requirements include, but are not limited to the following specialized security screenings: Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.

Requirements

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• 2+ years' professional experience in applications of computer science, with coding experience in Python.
• 2+ years' professional experience in designing, building, and maintaining scalable data pipelines and infrastructure.
• Experience in SQL databases.
• Demonstrated ability to perform in ambiguous environments and thrive in a dynamic work environment.
• Exceptional interpersonal and communication skills, especially the ability to explain complex issues clearly and concisely.

Nice To Haves

• Experience with Azure DevOps, Azure Data Factory, Databricks, and other Azure data services.
• Statistical background and/or data science experience.

Responsibilities

• Design, build, and maintain scalable data pipelines and workflows using Python and SQL to support data integration, transformation, and loading processes.
• Develop and manage Azure DevOps (ADO) pipelines and other Azure Infrastructure (subscription, blob storage, VMs, etc.) to automate deployment and integration workflows, ensuring efficient and reliable delivery of data solutions.
• Drive and enforce best practices in software development, including code reviews, testing, and continuous integration/continuous deployment (CI/CD) processes.
• Ensure data quality, integrity, and governance by implementing robust data validation, monitoring, and auditing processes.
• Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees