Senior Data Scientist Engineer

Cushman & Wakefield•Dallas, TX

6h•Hybrid

About The Position

The Senior Data Scientist Engineer will be a key member of the team responsible for the development and execution of a comprehensive data strategy aligned with the organization’s goals and objectives. This role involves turning raw data into actionable insights that drive business. The position is responsible for the ingestion, storage, modeling, and consumption of enterprise data, as well as leading the design of data solutions, ensuring good performance, scalability, and accuracy. The role also involves supervising and supporting the implementation of ETL pipelines, overseeing required configuration, and developing data migration and data engineering solutions utilizing Microsoft Azure products and services. Leveraging advanced AI/ML skills is crucial for uncovering trends, identifying opportunities, supporting strategic decision-making, and solving complex business problems. The Senior Data Scientist Engineer will serve as a subject matter expert with in-depth knowledge of quantitative methods and diligent knowledge of 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.
In the alternate, employer will accept 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 Data Lake Storage migrations.
Pull data from external sources using APIs & web scraping.