Senior Applied Machine Learning Engineer - Remote
FunnelStory (hiring via recruitment partner ClanX) seeks an applied ML engineer to own and improve production churn, retention, and account segmentation models on customer data — investigating prediction errors account by account and shipping improvements directly into the Go product codebase.
- Compensation
- Not disclosed
- Location
- Remote job
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Contract
- Experience
- 5+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 5+ years of applied ML experience with structured business data in production
- Strong foundations in mathematics and statistics from a rigorous academic programme
- Experience owning a production model used for business decisions (churn, retention, propensity, customer health, or segmentation)
- Strong understanding of classification, precision, recall, fixed test sets, and time-based evaluation
- Ability to identify and fix data leakage, incorrect labels, and weak features
- Experience working with messy CRM and product-usage data
- Strong SQL skills and engineering ability to ship changes inside a product codebase
- Ability to work with Go application code (Python allowed for analysis)
- Experience investigating individual prediction errors and explaining them to non-ML audiences
- Ability to independently drive unclear problems through investigation, testing, and implementation
- Candidate currently working at a product-based organisation
Nice to have
- IIT or similarly strong academic programme
- Public GitHub profile, side project, or technical blog
Full description
FunnelStory is hiring an Applied ML Engineer to improve production models for churn, retention, and account segmentation. Own prediction quality, investigate errors, and ship improvements customers can trust.
Company Details
FunnelStory brings customer data from multiple systems into a shared context graph, helping revenue teams and AI agents understand accounts and take permissioned actions. Its product uses account scores, cohorts, themes, and usage signals to support customer decisions.
Website:
Requirements
- 5+ years of applied ML experience with structured business data in production.
- Strong foundations in mathematics and statistics from a rigorous academic programme. An IIT or a similarly strong programme is preferred.
- Experience owning a production model used for business decisions, such as churn, retention, propensity, customer health, or segmentation.
- Strong understanding of classification, precision, recall, fixed test sets, and time-based evaluation.
- Ability to identify and fix data leakage, incorrect labels, and weak features.
- Experience working with messy CRM and product-usage data.
- Strong SQL skills and the engineering ability to ship changes inside a product codebase.
- Ability to work with Go application code. Python can be used for analysis, but improvements must reach production.
- Experience investigating individual prediction errors and explaining them to people without an ML background.
- Ability to independently drive unclear problems through investigation, testing, and implementation.
- A public GitHub profile, side project, or technical blog is a strong plus.
- Candidate currently working at a product based organisation is a must.
Responsibilities
- Improve existing churn, retention, and account segmentation models using customer data.
- Evaluate predictions against actual renewal, churn, expansion, and adoption outcomes.
- Build time-based backtests that prevent models from accessing future information.
- Investigate incorrect predictions account by account and identify gaps in labels, features, or source data.
- Ship improvements into the existing Go product, rather than stopping at analysis notebooks.
- Explain model performance and prediction errors to customers in clear business terms.
- Keep internal queries and training datasets confidential when discussing results.