Senior Data Scientist Demand Forecasting (fmd)

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 cant 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 were going: Today we own demand forecasting and stock management. Tomorrow: fully autonomous AI-driven procurement. Were not building features were rebuilding how modern commerce operates.

Why join now: Were a small fast team where every hire shapes the companys trajectory. Youll 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 isnt a maintenance role. Youll build the data foundation for a fully AI-driven future.

With high autonomy. At real data scale. With real impact.

What youll do

As a Senior Data Scientist Demand Forecasting youll own the core of our product: the VOIDS demand forecasting engine that currently forecasts of yearly revenue for our customers. Your mission is to solve our toughest challengedeveloping and continuously improving a scalable forecasting solution capable of accurately predicting demand for diverse e-commerce customers. Youll 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

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

What Youll Get

• Permanent full-time contract (no B2B)
• Competitive salary () 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