Data Science Innovation Lead - Forecasting Engine Utility

Key Skills

Aartificial intelligence, Agile methodologies, Algorithms, Machine learning techniques, PySpark, Python Programming

Job Description

Background & Purpose of the Job:

This Data & Analytics function endeavors to create clear accountabilities for all aspects of Data Strategy, Data Management, Information Management, Analytics, and Insights. We are accountable for impact of solutions, maintaining market relevance and minimizing unnecessary overlaps in analytics products, ensuring simplicity and that our solutions better meet the needs of our users. We partner with the Digital and Data Legal Counsel to ensure that our Data Defense (Privacy, Governance, Quality, etc.) is well structured and sufficiently robust to use data and AI correctly throughout the enterprise. We democratize information across the business, while supporting the culture shift required for data driven decision making.

Our vision is to make Unilever data intelligent, partnering with the business to power key decisions with data, advanced analytics and AI to accelerate growth. Our 5 strategies to achieve this are:

• Accelerate & simplify access to relevant data, information and insights
• Build in-house, leading-edge data, information, insights & analytics capability
• Lead the data & insightsculture and careers to empower employees across Unilever
• Rapidly embed analytics products, solutions and services to drive growth
• Advance Information Automation at Scale

Who You Are & What You’llDo

The Lead Data Scientist is an exciting role in the Data Science Centre of Excellence (CoE) team within D&Aa. This team builds state of the art machine learning algorithms, maximising the impact of D&A’s solutions in driving enterprise performance. Typical initiatives include building a state of art enterprise scale demand forecasting engine, optimizing trade promotion investments, accurately forecasting customer demand, using NLP to glean insight on consumer trends from search data, and making individual assortment recommendations for each of the millions of stores that sell Unilever products. The role will work closely with a D&A functional team such as Customer Development or Supply Chain along with business stakeholders, addressing both large transformation programs and near-term business problems.

• Lead the data science innovation work stream for Forecast Engine Utility and Integrated Business operations to deliver global forecast KPIs
• Develop and Govern innovation landscape against enterprise level one-forest solution together with business team such as digital supply chain, Sales & Operations planning, integrated customer development team
• Research and develop algorithms/Model to improve large scale demand forecasting problem (+billions of timeseries). Build, maintain, and improve new and existing suite of algorithms and their underlying systems.
• Lead technical design sessions; innovative problem solving, Document and Develop technical solutions aligned with business objectives; identify gaps between the current and desired end-states
• Analyzing the AI/ML algorithms that could be used to solve a given problem and ranking them by their success probability.
• Engaging in strategic discussions to identify problems while measuring and improving the quality of workflows. Identify and implement opportunities to improve tooling and implementation of scalable solutions
• Actively contribute to and re-use UL DS community best practices.
• Contribute to the AI innovation and build thought leadership via publications/patents and presence in industry/academic conference. Further, actively contribute towards establish innovation team as thought leader in demand forecasting within the CPG industry.
• Working in an agile environment with globally distributed teams.
• Mentor and supervise team member across the organization.

What You Need to Succeed

• Minimum of B.S. in a relevant technical field (e.g. Computer Science, Statistics, Engineering, Operations Research); preferably a postgraduate (Masters or Doctorate) degree
• 8+ years experience building data science solutions to solve business problems, preferably in the CPG industry (or 7-8 years for those with a PhD)
• Experience with open source languages (eg. Python) and equivalent tools for distributed computing (PySpark)
• Experience deploying solutions in a modern cloud-based architecture
• Experience managing the work of team members and 3rd party resource vendors
• Experience presenting insights and influencing decisions of senior non-technical stakeholders.