At a Glance
- Tasks: Lead the development of innovative Causal AI forecasting systems to enhance decision-making.
- Company: Join Cisco, a global leader in technology and innovation.
- Benefits: Enjoy competitive pay, remote work options, and generous volunteer time off.
- Why this job: Make a real impact in revolutionising demand forecasting with cutting-edge AI technology.
- Qualifications: 6+ years in Advanced Analytics; strong AI and machine learning skills required.
- Other info: Collaborative culture with opportunities for mentorship and career growth.
The predicted salary is between 48000 - 84000 £ per year.
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 effectively. We are a bright, engaged, and friendly global 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.
You Will
- 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 enhance 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 challenging 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 skillsets 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 realising 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.
#WeAreCisco where every individual brings their unique skills and perspectives together to pursue our purpose of powering an inclusive future for all. Our passion is connection—we celebrate our employees’ diverse set of backgrounds and focus on unlocking potential. Cisconians often experience one company, many careers where learning and development are encouraged and supported at every stage. Our technology, tools, and culture pioneered hybrid work trends, allowing all to not only give their best, but be their best. We understand our outstanding opportunity to bring communities together and at the heart of that is our people. One-third of Cisconians collaborate in our 30 employee resource organizations, called Inclusive Communities, to connect, foster belonging, learn to be informed allies, and make a difference. Dedicated paid time off to volunteer—80 hours each year—allows us to give back to causes we are passionate about, and nearly 86% do! Our purpose, driven by our people, is what makes us the worldwide leader in technology that powers the internet. Helping our customers reimagine their applications, secure their enterprise, transform their infrastructure, and meet their sustainability goals is what we do best. We ensure that every step we take is a step towards a more inclusive future for all. Take your next step and be you, with us!
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.
Title : Lead/Senior Data Scientist employer: Cisco Systems, Inc.
Contact Detail:
Cisco Systems, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Title : Lead/Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees at Cisco or in the data science field on LinkedIn. Ask them about their experiences and any tips they might have for landing a role. Personal connections can make all the difference!
✨Tip Number 2
Prepare for those interviews! Brush up on your Causal AI knowledge and be ready to discuss how you can apply it to real-world problems. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 3
Showcase your projects! If you've worked on relevant data science projects, create a portfolio that highlights your skills in Python, machine learning, and causal modelling. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the Cisco team. Let’s get you that job!
We think you need these skills to ace Title : Lead/Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead/Senior Data Scientist role. Highlight your experience with Causal AI and any relevant projects that showcase your skills in demand forecasting and machine learning.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data science and how your background aligns with our mission at Cisco. Be sure to mention specific experiences that relate to the job description.
Showcase Your Technical Skills: Don’t forget to highlight your technical skills, especially in Python, SQL, and machine learning. We want to see how you’ve applied these skills in real-world scenarios, so include examples of your work or projects.
Apply Through Our Website: We encourage you to apply through our website for the best chance of being noticed. It’s the easiest way for us to keep track of your application and ensure it gets to the right people!
How to prepare for a job interview at Cisco Systems, Inc.
✨Know Your Causal AI Inside Out
Make sure you brush up on your understanding of Causal AI and its applications in demand forecasting. Be ready to discuss how you've used these techniques in past projects, and think about specific examples where your insights led to improved decision-making.
✨Showcase Your Data Skills
Prepare to demonstrate your expertise in Python, SQL, and data engineering. Bring along examples of your work that highlight your ability to wrangle and analyse complex datasets, especially in real-time scenarios. This will show that you can handle the technical demands of the role.
✨Communicate Clearly and Effectively
Practice explaining complex concepts in simple terms. You’ll likely need to communicate your findings to non-technical stakeholders, so being able to articulate your thought process and results clearly is crucial. Think of ways to tell a compelling story with your data.
✨Be Ready for Problem-Solving Challenges
Expect to face some challenging problems during the interview. Prepare by reviewing case studies or hackathon experiences where you had to apply machine learning solutions. Show your thought process and how you approach problem-solving, as this will be key to impressing the interviewers.