About the role
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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