Experienced Data Scientist for Agentic Applications

Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Data Engineering

In short

Arla Foods søger en erfaren Data Scientist til at forme AI-drevne forretningsmuligheder og udvikle intelligente agentiske produkter. Du vil arbejde med prissætning, promotion, forecasting og Machine Learning modeller i et dedikeret produktteam, med mulighed for at operationalisere løsninger og identificere nye AI-muligheder.

Responsibilities

Design and develop statistical, econometric, and machine learning models for business insights.
Apply ML models and inference techniques to evaluate commercial initiatives and identify revenue opportunities.
Develop and operationalize forecasting, pricing, and promotional effectiveness models.
Partner with engineers and architects to establish scalable MLOps, model monitoring, and AI-enabled development practices.
Identify and mature new AI and Data Science opportunities into trusted business capabilities.

Requirements

Hands-on experience with Data Science, Machine Learning, Data Engineering, and modern AI tooling.
Strong experience with Bayesian hierarchical models using tools such as PyMC, Stan, or NumPyro.
Solid statistical inference and model validation practices.
Strong econometrics and causal inference expertise, including price elasticity modelling and endogeneity challenges.
Strong Python and SQL skills.
Experience deploying and maintaining models through automated pipelines, monitoring, testing, versioning, and MLOps practices.
Practical experience with machine learning approaches such as XGBoost, LightGBM, and forecasting techniques.
Daily use of AI-enabled development tools such as Claude, Codex, GitHub Copilot, or similar.
Product-oriented mindset and ability to translate business opportunities into scalable analytical solutions.

Desired Qualifications

Experience with Pricing, Promotions, Revenue Growth Management, Commercial Intelligence, or Net Revenue Management.
Experience with Optimization techniques and decision modelling using tools such as OR-Tools, Pyomo, or Gurobi.
Experience with advanced causal inference methods such as Causal Forests, Synthetic Control, Bayesian Structural Time Series, DoubleML, or EconML.
Experience with time-series forecasting approaches such as state-space models or Prophet.
Experience with Databricks, Spark, Azure, and modern cloud-based data platforms.
Experience with retail and consumer datasets.
MSc/PhD within Statistics, Econometrics, Data Science, Mathematics, or a related discipline.

Benefits

Flexible hybrid working model.
Competitive salary and benefits.
Opportunities for professional development in a rapidly evolving AI landscape.

Skills

PythonSQLMachine LearningData EngineeringBayesian hierarchical modelsPyMCStanNumPyroStatistical inferenceModel validationEconometricsCausal inferencePrice elasticity modellingXGBoostLightGBMDemand forecastingForecastingClaudeCodexGitHub CopilotMLOpsDatabricksSparkAzureState-space modelsProphetOR-ToolsPyomoGurobiCausal ForestsSynthetic ControlBayesian Structural Time SeriesDoubleMLEconML

#AI#Data Science#Machine Learning#Agentic Applications#Pricing#Promotions#Forecasting#Commercial Intelligence#Net Revenue Management

About Arla

We are more than 23,000 colleagues across 39 countries and 7,624 dairy farmer-owners in Denmark, Sweden, United Kingdom, Germany, Belgium, Luxembourg, and the Netherlands. We aim to create the future of dairy, to bring healthy and sustainable dairy products to people across the world, and to lead the transition towards sustainable dairy farming and production. We work continuously on the farms, at the dairies, and in our administration to reduce our carbon footprint and environmental impact. We are committed to champion good food habits and inspire a healthy life. We collaborate with NGOs and…

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