Advanced Data Scientist

Albertsons Companies is transforming how we operate from Source to Table, reimagining planning, ordering, inventory, and execution as a deeply connected, AI-enabled ecosystem. In this role, you will own the technical roadmap for an AI-native Data Science organisation that builds the predictive, prescriptive, and agentic intelligence powering our next-generation supply chain and store execution platforms.

Responsibilities:

• You will define and implement the overarching data science and AI architecture and technical strategy for a team of data scientists that will build data science and AI capabilities to optimize operations, processes and capabilities in Source to Table transformation area that would include: end to end demand forecasting; inventory optimization to minimize out of stocks; store and warehouse replenishment to minimize supply chain waste; Agentic AI frameworks to augment and automate planning and execution capabilities.
• You will be hands-on with design, implementation, and deployment of data science and AI models to convert multiple point solutions to connected data science and AI solutions at scale.
• Stay current with the latest advancements in data science, machine learning, and AI technologies.
• Evaluate and implement new tools and technologies to enhance the data science architecture and continuously improve analytical capabilities.
• Drive innovation through research, experimentation, and prototyping.
• Build and scale AI-native components: models + agents + reasoning layers.

Build a portfolio that includes:

• Lead partnerships with cross-functional teams, including product, engineering and domain experts, to deliver analytical, predictive and decision-support solutions for supply chain and fulfilment-related functions and capabilities.
• Interface with cross-functional leaders and represent points of view from data science to drive measurable success.
• Recruit, build and lead high-performing teams of data scientists in a technical capacity.
• Inspire and deliver data science innovations that fuel the growth of the business
• Provide technical and thought leadership in data science and AI.
• Guide architectures, data science models, machine learning algorithms and engineering best practices.
• Provide technical mentorship and guidance to the data science team.
• Use machine learning and AI to solve real customer problems, power the next generation experiences for large-scale applications in real time.
• Deliver breakthrough benefits to customers using personalised, enriched, and derived data from a range of sources.

Drive meetings and lead discussions:

• Prioritise projects across the team and allocate resources to meet business and team goals.
• Communicate sophisticated machine learning and modeling solutions and capabilities effectively with intuitive visualizations for business stakeholders.
• Core ML/optimization models (forecasting, bias correction, replenishment, shrink/markdown, execution signals).
• Agentic AI frameworks that augment and automate planning and executionhuman-in-the-loop where needed, autonomous where safe/valuable.
• LLM-powered explanation and decision support that translates outputs into natural language.

Requirements:

• Advanced degree in a STEM field like CS, DS, Engineering, Statistics, Math, etc. is preferred, or equivalent experience.
• PhD strongly preferred in Computer Science, Machine Learning, Statistics, Operations Research, Applied Mathematics, Industrial Engineering, or a closely related quantitative field (or equivalent depth of research + applied production experience).
• 3+ years of industry experience in applying data science: experimental design, machine learning, deep learning algorithms, operations research, applied mathematical optimisation, etc., at scale.
• Specific experience and skills working in the retail and grocery industry are preferred, including in the areas of supply chain optimisation, merchandising and pricing, digital/ecommerce, fulfilment, and customer and marketing analytics and intelligence capabilities using data science, AI and machine learning tools and techniques.
• You will bring product thinking and deep expertise in systems design to this role.
• You will bring an understanding of how planning and operations connect with customer-related work from a data science perspective.
• You would have prior experience as a consultant and bring a service mindset to the work of business transformation.
• You will be equally comfortable interacting with scientists, engineers, product, and business clients.
• Business acumen and retail understanding are critical.
• Getting stuff done is critical.
• Has to be able to clearly set a vision to partners for the art of the possible.
• Track record of guiding teams through unstructured technical problems to deliver business impact.
• Ability to translate high-level business objectives into action
• Skilled at running cross-functional relationships and communicating with leadership across multiple organisations.
• 3+ years of experience and proficiency in Python, SQL
• 3+ years of hands-on experience in building data science solutions and production-ready systems on big data platforms such as Snowflake, Spark, Hadoop
• 3+ years of experience with Data Engineering, MLOps, and Model Life Cycle Management.
• Excellent communication skills, with the ability to synthesise, simplify and explain complex problems to different audiences.
• Experience with logistics and supply chain management systems; Snowflake and Azure Databricks is a plus.
• Proven track record of leading data science projects and teams to architect and deploy data science solutions at scale.

Skills Required:

• Machine learning
• Deep learning
• Applied Optimisation, Operations Research
• Python
• SQL
• AI/machine learning tools (Databricks, Vertex AI, etc. )
• Systems design
• Analytics across functions
• Data Science team leadership (5+ years)
• Strong cross-functional relationship management and executive communication skills

Skills Preferred:

• Big data platforms (Snowflake, Spark, Hadoop)
• Data Engineering
• MLOps
• Model Life Cycle Management
• Experimental design
• Strategic retail and grocery analytics expertise

Skills

data science, databricks, deep learning, hadoop, machine learning, mlops, operations research, optimization, python, snowflake, spark, sql