Senior Data Scientist Engineer
About The Position
Cushman & Wakefield U.S., Inc. is seeking a Senior Data Scientist Engineer to join their team. This role is crucial for developing and executing a comprehensive data strategy aligned with organizational goals, transforming raw data into actionable insights that drive business decisions. The engineer will be responsible for the ingestion, storage, modeling, and consumption of enterprise data, leading the design of data solutions with a focus on performance, scalability, and accuracy. They will also supervise and support the implementation of ETL pipelines, oversee required configurations, and develop data migration and engineering solutions using Microsoft Azure products and services. Leveraging advanced AI/ML skills, the role involves uncovering trends, identifying opportunities, supporting strategic decision-making, and solving complex business problems. The ideal candidate will be a subject matter expert with in-depth knowledge of quantitative methods and data sources and tools.
Requirements
- Master’s degree or foreign equivalent in Computer Science, Information Technology, Data Science, or other directly related field of study; plus 2 years (24 months) of experience in the offered position or other closely related positions.
- OR Bachelor’s degree or foreign equivalent in Computer Science, Information Technology, Data Science, or other directly related field of study; plus 5 years (60 months) of experience in the offered position or other closely related positions.
- Experiences may be concurrent.
- Travel to various US office locations to engage the business in person (15%).
Responsibilities
- Optimize Azure Data Lake Storage (ADLS Gen2) to store and manage raw and processed data efficiently, ensuring proper access control and data security.
- Build and manage Azure Data Synapse/Azure Data Factory pipelines to orchestrate complex data workflows.
- Monitor the execution of data pipelines in the production environment and troubleshoot and return failures to service, supporting real-time integrations, and ensuring the availability and reliability of our data.
- Develop and maintain data models that support business needs, leveraging PySpark for data manipulation and transformation.
- Support business teams as a subject-matter expert on Data Migration and maintenance best practices.
- Work in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems.
- Assist with the development of the business case for requested system enhancements.
- Design, develop, implement and maintain analytical models and solutions using Machine Learning, AI and other advanced analytical capabilities to support business objectives.
- Conduct complex data analyses and communicate & visualize results to drive business insights and support more effective decision-making.
- Collaborate with stakeholders (data science and product teams) to drive solutioning and POC discussions.
- Serve as a subject matter expert to improve the organization's systems and/or processes related to Machine Learning, Deep Learning, Responsible AI, Gen AI, Natural Language Processing, Computer Vision and AI practices.
- Design, develop, test, deploy, maintain, and improve machine learning system software.
- Perform data mapping, profiling and processing activities to support the source system to Data Lake Storage migrations.
- Pull data from external sources using APIs & web scraping.
Benefits
- health, vision, and dental insurance
- flexible spending accounts
- health savings accounts
- retirement savings plans
- life, and disability insurance programs
- paid and unpaid time away from work
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What This Job Offers
Job Type
Full-time
Career Level
Senior
