Data Analytics Specialist

Mission of the Role (What you will be doing)

The Data Analytics Specialist is responsible for the development and maintenance of insight generating tools. The scope of work will include the creation of new data models in our data warehouse environment, the implementation of KPI dashboards that will provide answers to key business questions, and use of advanced analytics methods to solve pressing business problems. As a member of the Data and Analytics team, the Data Analytics Specialist will work closely with the Director of Data and Analytics to provide timely data driven solutions for SupplyOne’s Business Units and ancillary functions. The role requires a high degree of versatility and willingness to stay up to date with the latest industry trends and best practices. The incumbent analyst will gain hands on experience with implementing descriptive, predictive, and prescriptive data solutions and will also assist with the upkeep of the overall data platform.

Key Duties & Accountabilities

• Collaborate with business experts across the organization to understand specific needs.
• Implement sustainable and scalable data models that meet the needs of our business stake holders.
• Create visually appealing and intuitive dashboards that will facilitate the generation of key business insights.
• Experimentation with various python machine learning models to solve complex business problems (i.e., XGBoost, Random Forest, DNN etc.).
• Implement machine learning models to Azure Machine Leaning Service.
• Educate business users to enhance data literacy across the organization.

Essential Functions

• Participate in peer code review sessions to ensure adherence to team standards.
• Monitor the performance of all implemented data solutions.
• Remain up to date with emerging trends in data analytics and machine learning.
• Ensure that all data solutions are implemented using industry and company best practices.

Educational/Training Requirements/Experience (What your background should look like)

• BS in information systems, computer science, data analytics or any related field of study or 1-2 years of applicable project experience.
• Demonstrable experience with writing SQL queries of at least medium complexity.
• Possess a solid understanding of core data modeling principles within a data warehouse environment. i.e., facts and dims.
• Experience with building dashboards to track key performance indicators.
• Basic understanding of data science/machine learning concepts (i.e., supervised learning vs unsupervised learning, model training, etc.).
• Experience building predictive models in python.
• Experience building ETL/ELT data pipelines.
• Working knowledge of cloud computing services for data analytics and productivity.

Minimum Skills, Knowledge & Ability Requirements

• SQL.
• Python.
• Machine Learning Libraries (scikit learn, Keras, MLlib, pyOD etc.).
• Tableau, Power BI, Looker, or any data visualization tool.
• Azure Cloud Service.