Senior Data Scientist, Cisco

Job Description

Cisco is searching for a Senior Data Scientist who will work with its Forecasting Data Science Team in Global Planning. The position develops Causal AI solutions which transform enterprise Demand Forecasting methods by enhancing operational accuracy and efficiency and delivering better prescriptive insights to Cisco supply chain and operations. The job requires handling multiple datasets while implementing advanced machine learning models and working with international teams to create solutions for large-scale enterprise use.

Experience: 6+ years with Master’s or 4+ years with PhD

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Main Duties:

• Develop, maintain, and evolve Causal AI-based forecasting systems for aggregated demand.
• Analyze global financial, macroeconomic, and competitive factors to improve causal considerations in forecasting models.
• Engineer features from internal and external structured and unstructured datasets, uncovering causal relationships for structural models.
• Build high-quality, robust, and long-lived ML models for enterprise-scale applications.
• Collaborate with Global Planning, Finance, Supply Chain, and business leads to integrate insights into decision-making.
• Research and implement uncertainty quantification and reconcile forecasts across hierarchies, time horizons, and methodologies.
• Mentor junior data scientists and engineers, shaping skills and fostering innovation within the team.

Essential Qualifications:

• Foundation in AI technology and Machine Learning methods and Causal ML techniques. 
• Advanced skills in Python and SQL together with data engineering expertise and also have experience using version control through Git. 
• Ability to handle data through the processes of cleaning and analyzing and extracting insights to create machine learning solutions. 
• Excellent problem-solving abilities with communication skills and storytelling ability to explain difficult technical ideas to others.

Preferred Skills:

• Expertise in international financial systems, macroeconomic conditions and econometric data. 
• Practical knowledge of working with Structured Causal Models and time-series forecasting methods. 
• Demonstrates expertise in data science through their successful leadership and mentorship of data science initiatives. 
• Expertise in developing analytical solutions that meet business needs through their ability to transform business requirements into practical analytics solutions.