Head of Applied Science
Rohlik · 🌍 München, Germany
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- Can’t check pay against the visa rulesNo salary stated. Germany EU Blue Card needs at least €50,700 a year (shortage-occupation / recent-graduate: €45,934). Source: https://www.make-it-in-germany.com/en/visa-residence/types/eu-blue-card, rules effective 2026-01-01.
- Confirmed live todayWhen a source last listed this job as open.
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No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.
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Sponsor Radar — Rohlik
This employer posted directly and does not match a government sponsor register.
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About the role
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 exciting • Direct 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 deliver • Business 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 for • Track 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 prob