Head of Applied Science

Rohlik is the leading Central European e-grocer. More than a million customers shop with us across Rohlik.cz, Knuspr.de, Kifli.hu, Gurkerl.at, and Sezamo.ro, choosing from over 20,000 items delivered within hours in 15-minute windows. Behind every order is a continuous stream of automated decisions: how much inventory to buy for each warehouse, how many pickers to schedule on Thursday morning, where in the warehouse a product should sit, and which van carries which bags. Our models make these choices every day across five countries. When a forecast is accurate, shelves stay full and waste is minimized. When a plan is right, warehouses run on exact labor needs and orders arrive precisely in the customer’s chosen window. Get it wrong, and it immediately translates into shrink, overtime, tied-up capital, and missed customer deliveries. Why this role is excitingDirect operational and business impact: Your team’s models directly drive availability, shrink, fulfillment costs, and working capital across all five markets. True ownership with zero friction: We operate automated production pipelines with no committee between your team and deployment—a solid backtest is all you need to ship. Unification of two core capabilities: You will bring Forecasting and Optimization into a single function, building an end-to-end decision-making ecosystem from the ground up. AI-first environment: Our engineers use AI coding agents (Devin, Claude Code) daily, and we expect you to push the boundaries of modern agentic workflows and tooling. Direct executive exposure: Reporting directly to the Group CTO, you will have the mandate and space to shape technical strategy and execution. What you will own and deliverBusiness outcomes: Own the business results delivered by the forecasting and optimization portfolio, setting targets with cell leads and tracking financial and operational impact in production. Strategic roadmap & prioritization: Define which decisions to automate next across purchasing, fulfillment center planning, workforce scheduling, and commercial optimization (promotions, markdowns, demand shaping). Technical standards & architecture: Set the bar for problem framing, method selection, fast production MVPs, honest evaluation/backtesting against business metrics, and reliability monitoring. Function unification & leadership: Merge Forecasting and Optimization into one high-performing team; set hiring standards, develop ML engineers and applied scientists, and foster an AI-first way of working. Cross-functional partnership: Partner closely with cell leads, operations managers, product owners, and engineering leads to align on business metrics, baselines, and seamless system integration. What we are looking forTrack record of impact: 8+ years applying machine learning, forecasting, or operations research to real operational or commercial problems, with clear metrics demonstrating business results. Works backwards from outcomes: A proven habit of defining target metrics first, selecting the simplest effective method, shipping fast MVPs, and iterating in production. Hands-on technical depth: Experience building and shipping production models in time-series/probabilistic forecasting or mathematical optimization (LP, MIP, CP, heuristics, simulation), with enough depth to review models and judge when simple heuristics beat complex models. Technical skills: Fluency in Python and SQL; hands-on experience with production pipelines, monitoring, and backtesting; familiarity with modern forecasting stacks or solvers (Gurobi, CPLEX, OR-Tools). Operational fluency: Experience working directly alongside supply chain, warehouse, or logistics operations, including spending time on the floor to understand problems before framing models. Leadership & communication: Proven experience leading technical teams, hiring top talent, developing engineers, and translating complex model mechanics into business trade-offs for executives. AI-first mindset: