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

Tasks

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 develop and continuously improve a scalable forecasting solution capable of accurately predicting demand for diverse e-commerce customers. You will handle varied and dynamic datasets, numerous input variables, shifting market behaviours, and volatile trends.

• 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

• Decide what to focus on 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 and inference, using tools such as Airflow, Dagster, AWS SageMaker, and MLflow

• Hands‑on experience with SQL databases, ideally PostgreSQL

• Delegating work to entire AI workflows and shipping AI‑enabled data and modelling pipelines where actual decisions and work are done by 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, covering the full data pipeline more full‑stack

• Familiarity with infrastructure frameworks (Terraform, Kubernetes, etc.)

• Exposure to technologies for handling larger data sets such as BigQuery and Spark

• Contributions to developer experience and internal tooling improvements

• Practical experience with forecasting tools such as Nixtla, Darts, statsmodels, and sktime

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

• Permanent full‑time contract (no B2B)

• Competitive salary (€80,000–€100,000) + Equity

• 30 days paid vacation

• All AI subscriptions with unlimited usage

• New MacBook Pro & minimum two 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