Data Scientist

Key Responsibilities:

• Design and develop new algorithms to support real-time recommender systems
• Work, as directed, on developing analytical models to support strategic management decision-making
• Maintain and enhance existing forecasting models; build new models to incorporate user feedback and Google Analytics data.
• Work on ad-hoc analysis and handle data requests from business stakeholders.
• Provide support for existing analytical processes and meet stakeholders' service expectations.
• Maintain asset bundles and API endpoints for production-level models.
• Develop and maintain good documentation of code and processes. Assist in writing user manuals, as needed.
• Prepare commentary around findings and implications of analysis.
• Bridge operational analytics to financial impacts, participate in project-based initiatives, and perform other duties as assigned.

Key Skills:

• Proficiency in programming languages such as Python, R, and SQL for data manipulation and model development.
• Strong understanding of machine learning algorithms, including recommender systems, forecasting models, and predictive analytics.
• Experience with data visualization tools (e.g., Power BI or similar) for presenting insights.
• Familiarity with cloud platforms and ML Ops practices for deploying and maintaining models in production.
• Familiarity with Code Management and Version Control(Git, ADO, etc.)
• Knowledge of API development and integration for real-time model consumption.
• Expertise in statistical modeling, hypothesis testing, and experimental design.
• Ability to work with large datasets, perform data cleaning, and ensure data quality.
• Experience with digital analytics tools (e.g., Google Analytics) and customer behavior analysis.
• Excellent written and verbal communication skills for preparing commentary and documentation.
• Experience with Databricks asset bundles and ADO pipelines