Senior/Lead Data Scientist (AI)

TL;DR

Senior/Lead Data Scientist (AI): Building and optimizing new products that translate customer signals into actionable insights and measurable outcomes, with an accent on turning human signal into product performance and establishing robust experimentation frameworks. Focus on productionizing and scaling durable data and model workflows in collaboration with engineering, ensuring system reliability, explainability, and evolvability.

Location: Hybrid (Vauxhall, UK)

Company

hirify.global helps brands identify true promoters, activate authentic recommendations, and align teams around Voice of Customer insights to drive profitable growth.

What you will do

• Build components for new products converting real customer signals into timely actions and measurable outcomes.
• Partner across Product, Engineering, CS, and Commercial to make the human signal visible, actionable, and compounding.
• Establish experimentation and measurement foundations, designing how to test, learn, and prove impact with sound statistical practice.
• Productionize and scale durable data and model workflows in collaboration with the engineering team.
• Ensure quality and monitoring, and document decisions for a reliable, explainable, and evolvable system.

Requirements

• Track record, typically 4+ years, in applied data science for product or marketing in consumer or SaaS.
• Continuous learning mindset, staying current with generative AI advances and prototyping with new models.
• Hands-on ML skills: feature engineering, propensity or uplift modeling, model evaluation, monitoring.
• Strong Python and SQL with the ability to move from notebooks to production code.
• Practical data engineering instincts: event schemas, batch jobs, orchestration, data quality guardrails.
• Clear communication that translates complexity into actionable narratives for non-technical audiences.

Nice to have

• LLM applications for agentic solutions.
• Graph modeling.
• Personalization: propensity/uplift modeling, bandits, causal inference.
• Experience with dbt, Airflow, Looker or Metabase, AWS services such as S3 and Lambda.
• Experience in designing and implementing model/metric endpoints (e.g., FastAPI/Flask, OpenAPI).

Culture & Benefits

• Hybrid work with in-person collaboration at Vauxhall HQ and flexibility for focused work.
• Cross-functional by default with close partnership across Product, Engineering, CS, and Commercial.
• Outcome-driven approach with small releases, fast validation, and scaling what works.
• Access to various perks and benefits mentioned by the company.