Senior Data Scientist (Time Series + ML) | 6+ Years

Cisco Systems · Hardware & Semiconductors

Bangalore, India
On-site
Posted today
Data & AI

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About the job

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 pioneering the application of Causal AI to revolutionise 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 optimally.

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 recognised this team in their Power of Profession 2024 Supply Chain awards as one of the top 5 in the Process and Technology Innovation category.

Your Impact

You will bring your skills, experience, and innovation to play a significant role in shaping our Causal AI-based forecasting system to improve decision making and drive operational performance and efficiency across Cisco’s Enterprise and Supply Chain functions.

Responsibilities : -

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

Analyse and sharpen the causal consideration of global financial markets, macro-economics, micro-economic and competitive factors in the Demand Forecasting models.

Engineer model features from broad internal and external structured and unstructured datasets, discover and improve the natural segmentation for Demand based on these factors, resolve causality of the factors, and incorporate them into structural causal models.

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

Solve complicated research problems that push the boundaries of structural causal modelling and scale to Enterprise and Supply Chain business applications.

Work closely with business leads and experts in Global Planning, other Supply Chain functions, Finance, and other Cisco organisations to understand relationships and patterns driving Cisco demand.

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

Research and develop new methods to reconcile between forecasts at multiple product hierarchy levels, multiple time horizons, and different forecasting approaches.

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

Provide technical direction and mentoring to junior data scientists and data engineers in the team, helping shape the skills and values of the next generation of Cisco data scientists.

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.

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

Expertise in Python, with sophisticated 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 sophisticated 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.

Meaningful experience using Causal AI and Structured Causal Models in time series settings.

Meaningful experience in time series forecasting for demand use cases and/or other sophisticated wide-ranging 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 realising feasible data science solutions.

Demonstrated team leadership, project management, and business partner influencing skills

Experience mentoring team members to improve their own technical and project management skills.

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Disclaimer

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be in direct response to an application you have submitted through the company career site

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