Cisco Applied Data Scientist 

United States, Georgia, Atlanta 

921318456

THE DIFFERENCE YOU WILL MAKE:

Develop, evolve, and sustain key elements of the Causal-AI based Forecasting system for Aggregated Demand.

- Develop high-quality, accurate, economical models that are robust and have a long shelf-life.

- Improve the efficiency and scalability of the Forecasting System.

- Engineer model features using these factors, discover and enhance the natural segmentation for Demand based on these factors, determine the causality of the factors, and incorporate them into structured causal models.

- Develop and evolve reliable approaches for uncertainty quantification to enable scenario/range forecasts.

- Leverage and incorporate appropriate machine learning approaches including customization of recently published research as needed to build better Causal AI solutions.

- Connect with partners to communicate the short- and long-term AI forecasts and the changes in these forecasts. Discern and articulate the story in the forecasts and forecast changes, areas of discrepancies or differences with expert forecasts, understanding, and accounting for the confidence level of these forecasts.

4+ years of Advanced Analytics experience with a Masters degree or equivalent, or 2+ years with a Ph.D. in a Quantitative field leveraging statistical and machine learning methods in the thesis.

- All-round foundation in AI and machine learning, with a theoretical and practical understanding of Causal machine learning approaches.

- Expertise in Python, with advanced data analysis and data engineering skills, including using SQL

- Expertise and understanding of statistics and causal inference in time series settings

- Critical thinking, with a sharp eye for patterns and the skills to draw out the story and conclusions from data and modeling experiments in real-time.

- Experience with global financial markets, macro-economics, micro-economics, econometrics, and Corporate Finance preferred

- Experience in developing and operationalizing scalable ML solutions in cloud environments.

- Demonstrated structured wrangling and mining skills from data, and problem-solving skills using machine learning, including in real-time hackathon-like settings.

- Good communication and storytelling skills with an ability to unpack complex problems, and articulate AI/ML approaches, solutions, and results for non-technical audiences.