Fresha

4 weeks ago

Head of Data Science

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Build and solidify data science as a core function by setting the data science agenda, defining a roadmap aligned to marketplace, payments, and partner growth, and securing exec buy-in. Lead a small but strong team to ship production ML that drives measurable outcomes (fraud detection, text moderation, taxonomy classification), establish experimentation and experimentation platforms, and build foundational MLOps and data science infrastructure using SageMaker with dbt/Snowflake.

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Director level

Key Responsibilities

•Define the data science roadmap aligned to business priorities across marketplace, payments, and partner growth.
•Identify and prioritise data science opportunities that move revenue or cost, and make the case for investment at the exec table.
•Ship ML products that drive measurable business outcomes, and establish experimentation as a discipline (A/B testing, causal inference, automated experimentation).
•Build foundational data science infrastructure, including feature store, model governance, monitoring, and CI/CD for ML.
•Grow the function by championing data science across the business, scaling the team, and setting technical and cultural standards.

Key Requirements

•Track record of building a data science function from small into something the business relies on (not inheriting one).
•Shipped ML models to production at scale with measurable business outcomes.
•Exec-level communication: make the case for data science investment to C-suite, product, and commercial leaders.
•Technical depth to evaluate architecture, review work, and choose the right trade-offs.
•4+ years in data science or ML engineering, including 3+ years directly managing data science teams.

Skills:LeadershipExecutive communicationTechnical evaluationPrioritisationHands-on collaboration

Tech Stack:SageMakerSnowflakeDbtDockerMLOpsFeature storeModel governanceMonitoringCI/CDA/B testingCausal inference

Company Brief

Fresha

Fresha operates a global bookings and business management platform for salons, spas and beauty professionals, offering appointment scheduling, point-of-sale, payments, marketing tools and a consumer marketplace to connect clients with local services.

Industry: Enterprise Software

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: London, United Kingdom

Founded: 2015

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

Fresha

4 weeks ago

Head of Data Science

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Director level

Key Responsibilities

•Define the data science roadmap aligned to business priorities across marketplace, payments, and partner growth.
•Identify and prioritise data science opportunities that move revenue or cost, and make the case for investment at the exec table.
•Ship ML products that drive measurable business outcomes, and establish experimentation as a discipline (A/B testing, causal inference, automated experimentation).
•Build foundational data science infrastructure, including feature store, model governance, monitoring, and CI/CD for ML.
•Grow the function by championing data science across the business, scaling the team, and setting technical and cultural standards.

Key Requirements

•Track record of building a data science function from small into something the business relies on (not inheriting one).
•Shipped ML models to production at scale with measurable business outcomes.
•Exec-level communication: make the case for data science investment to C-suite, product, and commercial leaders.
•Technical depth to evaluate architecture, review work, and choose the right trade-offs.
•4+ years in data science or ML engineering, including 3+ years directly managing data science teams.

Skills:LeadershipExecutive communicationTechnical evaluationPrioritisationHands-on collaboration

Tech Stack:SageMakerSnowflakeDbtDockerMLOpsFeature storeModel governanceMonitoringCI/CDA/B testingCausal inference

Company Brief

Fresha

Industry: Enterprise Software

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: London, United Kingdom

Founded: 2015

Website LinkedIn