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. 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. 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. 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. 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
As a Senior Data Scientist – Demand Forecasting, you’ll own the core of our product: the VOIDS demand forecasting engine that currently forecasts €1,000,000,000 of yearly revenue for our customers. Your mission is to solve our toughest challenge—developing and continuously improving a scalable forecasting solution capable of accurately predicting demand for diverse e-commerce customers. You'll thrive in complexity, handling varied and dynamic datasets, numerous input variables, shifting market behaviors, and volatile trends. Specifically, you will:
- 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
- Enhance developer experience, advocating best practices, and upgrading tooling within the data science and engineering teams
- Run our forecasting operations, making sure fresh and stable models and forecasts are shipped to our customers reliably
- Actually get things done, deciding yourself what to focus on — without bureaucracy
Requirements ✅ Must-Have Skills
- 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
- Delegating work to entire AI workflows and shipping AI-enabled data / modelling pipelines where actual decisions and work is done by AI. We want to build a tech stack that can e.g. pick the right setup for a customer with the help of AI.
- Strong product and customer intuition and a proactive, ownership-oriented mindset
- Comfort with ambiguity and autonomy in problem-solving
Bonus / Nice-to-Have
- Experience with eCommerce and/or B2B SaaS startups
- Background in data engineering for scalable data pipelines, to cover the whole data pipeline more full-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.
Tech Stack
- Programming: Python (Pandas, Polars), SQL
- Modeling: Statistical, ML, and neural time series models (mostly Nixtla)
- Data Storage: PostgreSQL, AWS S3 (Parquet)
- ML Infrastructure: AWS SageMaker, AWS Lambda, MLflow
- Orchestration: Airflow on AWS
- Collaboration & AI Tools: GitHub Copilot, ChatGPT
Benefits 🎁 What You’ll Get
- Permanent full-time contract (no B2B)
- Competitive salary (€80,000–€100,000) + Equity
- 30 days paid vacation
- All AI subscriptions with unlimited usage you want
- New Mac Book Pro & min. 2 Monitors in the office ;)
- Regular team events and quarterly off-sites
- 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 talk to you and learn 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
- What motivates you, and what kinds of data problems you find genuinely interesting
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