Senior Data Scientist - Demand Forecasting (f/m/d)

Das ist der Job

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We forecast demand at the product level, catch stockouts and inefficiencies before they happen, and tell e-commerce teams exactly what to do — or execute it automatically with a click. We’re not building features — we’re rebuilding how modern commerce operates. Why join now: We’re a small, fast team where every hire shapes the company’s trajectory.

Enhance developer experience, advocating best practices, and upgrading tooling within the data science and engineering teams. Benefits All AI subscriptions with unlimited usage you want. Regular team events and quarterly off‑sites. We maximize product availability with minimal cashflow investment in 1/10 of the time.

We solve a real problem for SMEs. With AI. The problem we solve: Mid-size Shopify brands lose revenue and cash to stockouts and inefficiencies every day. They can see the problem. They can't fix it fast enough. What VOIDS does: VOIDS is the AI brain for mid-size Shopify brands. The result: 98% inventory efficiency. 20x ROI.

Six-figure cash unlocked. Within weeks. Traction: Launched June 2023. Since then: 300% growth, 1B+ data points processed, €2M ARR, 50+ brands live — including Hyrox, 6pm, Creamyfabrics, and NatureHeart. Now targeting €10M ARR by 2027. Where we’re going: Today we own demand forecasting and stock management.

Tomorrow: fully autonomous AI-driven procurement. You’ll work directly with Jannik and Tobias, two founders who live and breathe e-commerce and AI, and own how we ingest, process, and activate 1B+ data points across our platform. This isn’t a maintenance role. You’ll build the data foundation for a fully AI-driven future. With high autonomy.

At real data scale. With real impact. Tasks What you’ll do Develop the forecasting engine that fuels VOIDS demand forecasting services, directly influencing customer outcomes and satisfaction. Design and implement scalable forecasting methodologies adaptable to a diverse customer base and unique datasets.

Actively engage with customers, gathering deep insights and feedback to ensure our forecasting solutions meet their evolving needs. Collaborate closely with the CTO, CEO, customer success, and engineers. Identify and execute strategic improvements in scalability, accuracy, and performance of forecasting systems.

Run our forecasting operations, ensuring fresh and stable models and forecasts are shipped to our customers reliably. Decide what to focus on and get things done without bureaucracy. Requirements Fluent English communication skills; German is a plus.

Clear, professional, and asynchronous communication abilities. 3+ years of Data Science experience, including at least 2 years specifically in time series forecasting (preferably consumer products). Experience building and maintaining pipelines and APIs for model training/inference, using tools such as Airflow, Dagster, AWS SageMaker, MLflow, etc.

Hands‑on experience with SQL databases, ideally PostgreSQL. Ability to delegate work across AI workflows and ship AI‑enabled data/modeling pipelines where decisions are made by AI. Strong product and customer intuition and a proactive, ownership‑oriented mindset. Comfort with ambiguity and autonomy in problem‑solving.

Experience with eCommerce and/or B2B SaaS startups. Background in data engineering for scalable data pipelines, covering the full data stack. Familiarity with infrastructure frameworks (Terraform, Kubernetes, etc.). Exposure to technologies for handling larger data sets such as BigQuery, Spark, etc.

Contributions to developer experience and internal tooling improvements. Practical experience with forecasting tools such as Nixtla, Darts, statsmodels, sktime, etc. Modeling: Statistical, ML, and neural time series models (mostly Nixtla). ML Infrastructure: AWS SageMaker, AWS Lambda, MLflow. Orchestration: Airflow on AWS.

Collaboration & AI Tools: GitHub Copilot, ChatGPT. New MacBook Pro and at least two monitors in the office. Real ownership and influence. A calm, focused work environment that rewards initiative. Wellpass membership to unlimited fitness, yoga, swimming, climbing, and more.

We care less about titles and more about impact, so we look forward to talking to you and learning more about a forecasting model you built and what complexity you dealt with, how you currently use AI in your daily engineering workflow—concretely, not in theory—and what motivates you and the kinds of data problems you find genuinely interesting. #J-18808-Ljbffr