Plumb reconciles ad spend and subscription revenue into one number businesses can trust. The Forecasting team takes that a step further: projecting where spend, revenue, CAC, and retention are heading, so our customers can decide where the next dollar goes with confidence.
About the team
The Forecasting team is at a pivotal, high-growth stage. The core pipeline is built and working, and we’re now onboarding new, diverse customers quickly. This role is dynamic by nature: it takes technical depth, proactive research, and genuine communication skill to adapt our models to real customer data and real business challenges. You’ll be a critical link between the core product and our clients’ results.
What you’ll do
- Work at the forefront of forecasting subscription economics: projecting spend, revenue, CAC, and retention, and optimizing and deploying the models behind them.
- Tackle complex problems with state-of-the-art time-series techniques: model ensembling, anomaly detection, feature engineering for trend and seasonality, and causal inference.
- Partner closely with clients, diving into their unique datasets to understand the nuances and quirks of their business.
- Lead rigorous testing of our core ML pipeline on new customer data, finding where it excels and researching solutions where it doesn’t.
- Help clients reach and see the measurable value of Plumb’s forecasting, in numbers they can defend.
- Work in a production, product-oriented environment, keeping models robust, scalable, and integrated into the client’s workflow.
What we’re looking for
- 5+ years as a data scientist working on tabular and time-series data.
- BSc in a relevant field: Computer Science, Engineering, Statistics, or similar.
- Proficient in Python, SQL, and Spark.
- Proven experience creating measurable value with ML: defining KPIs, designing A/B tests, and monitoring models in production.
- Deep experience with time-series modeling and forecasting techniques.
- Comfortable working directly with customers in English.
Nice to have
- Experience with AWS or Databricks.
- An MSc or research background.