Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Senior / Lead Applied Data Scientist - Causal AI for Demand Forecasting.

Cisco
Greater London
1 month ago
Create job alert

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.


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.


You Will

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

Related Jobs

View all jobs

Senior / Lead Applied Data Scientist - Causal AI for Demand Forecasting

Lead/Senior Data Scientist

Senior Data Scientist (AI & ML)

Senior Data Scientist (AI & ML)

Chief Data Scientist

Senior Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.

Why Now Is the Perfect Time to Launch Your Career in Data Science: The UK's Analytics Revolution

The United Kingdom stands at the forefront of a data science revolution that's reshaping how businesses make decisions, governments craft policies, and society tackles its greatest challenges. From the machine learning algorithms powering London's fintech innovation to the predictive models guiding Manchester's smart city initiatives, Britain's transformation into a data-driven economy has created an unprecedented demand for skilled data scientists that far outstrips the available talent. If you've been contemplating a career transition or seeking to position yourself at the cutting edge of the digital economy, data science represents one of the most intellectually stimulating, financially rewarding, and socially impactful career paths available today. The convergence of big data maturation, artificial intelligence mainstream adoption, business intelligence evolution, and cross-industry digital transformation has created the perfect conditions for data science career success.

Automate Your Data Science Jobs Search: Using ChatGPT, RSS & Alerts to Save Hours Each Week

Data science roles land daily across banks, product companies, consultancies, scaleups & the public sector—often buried in ATS portals or duplicated across boards. The fix: put discovery on rails with keyword-rich alerts, RSS feeds & a reusable ChatGPT workflow that triages listings, ranks fit, & tailors your CV in minutes. This copy-paste playbook is for www.datascience-jobs.co.uk readers. It’s UK-centric, practical, & designed to save you hours each week. What You’ll Have Working In 30 Minutes A role & keyword map spanning Core DS, Applied/Research, Product/Decision Science, NLP/CV, Causal/Experimentation, Time Series/Forecasting, MLOps-adjacent & Analytics Engineering overlaps. Shareable Boolean searches for Google & job boards that strip out noise. Always-on alerts & RSS feeds that bring fresh UK roles to you. A ChatGPT “Data Science Job Scout” prompt that deduplicates, scores match & outputs ready-to-paste actions. A simple pipeline tracker so deadlines & follow-ups never slip.