Lead / Senior Applied Data Scientist - Causal AI for Demand Forecasting at Cisco Systems
London, England, United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

06 Jun, 25

Salary

0.0

Posted On

06 Mar, 25

Experience

4 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, Financial Markets, Applied Mathematics, Data Analysis, Econometrics, Physics, Python, Sql, Team Leadership, Project Management Skills, Economics, Business Requirements, Computer Science

Industry

Marketing/Advertising/Sales

Description

MEET THE TEAM

The post-pandemic years have exposed inherent biases and limitations in human-driven and statistical/Traditional ML-based forecasting approaches. Cisco wasn’t immune and saw a sharp increase in backlogs, inventory levels, and supply chain costs. The Forecasting Data Science Team within Global Planning is solving this by using Causal AI to redefine Demand Forecasting and its Enterprise impact. We’re working to provide breakthrough levels of regime-resilient forecast accuracy, efficiency, and prescriptive insights that enable decision makers across Cisco and its Supply Chain to plan effectively.
We are a bright, engaged, and friendly distributed team working with an industry-leading Causal AI ecosystem. Gartner has ranked Cisco’s Supply Chain to be #1 or #2 in the world over the last 5 years, and recognized this team in their Power of Profession 2024 Supply Chain awards as one of the top 5 in the Process and Technology Innovation category.

MINIMUM QUALIFICATIONS

  • 6+ years of Advanced Analytics experience with a Masters Degree or 4+ years with a PhD in a Mathematics or Applied Mathematics, Operations Research, Economics, Econometrics, Physics, Computer Science, Engineering, or related quantitative field.
  • Strong 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, experience git version control.
  • Demonstrated structured wrangling and mining skills from data, and problem-solving skills using machine learning, including in real-time hackathon-like settings.
  • Excellent communication and storytelling skills with an ability to unpack complex problems, and articulate AI/ML approaches, solutions, and results for non-technical audiences.

PREFERRED QUALIFICATIONS

  • Experience with global financial markets, macro-economics, micro-economics, econometrics, and financial datasets.
  • Substantial experience using Causal AI and Structured Causal Models in time series settings.
  • Substantial experience in time series forecasting for demand use cases and/or other complex or dynamic domains like marketing/pricing
  • A practical and effective approach to problem-solving using AI/ML and a knack for envisioning, translating business requirements into analytics requirements, and realizing feasible data science solutions.
  • Demonstrated team leadership, project management, and business stakeholder influencing skills
  • Experience mentoring team members to improve their own technical and project management skills.
Responsibilities

Please refer the Job description for details

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