Head of Data and AI

Jobgether • United Kingdom
Remote
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AI Summary

Lead the data science and AI function, building and managing a high-performing team to drive business outcomes through data insights and AI capabilities.

Key Highlights
Define the data strategy and roadmap for maximum business impact
Build, mentor, and manage a high-performing Data team
Partner with product, engineering, marketing, operations, and leadership to translate business goals into measurable outcomes
Key Responsibilities
Define the vision and roadmap for the data function, prioritizing initiatives for maximum business impact
Build, mentor, and manage a high-performing Data team while coordinating with external agencies until internal resources are established
Partner with product, engineering, marketing, operations, and leadership to translate business goals into measurable outcomes
Lead applied AI/LLM initiatives, including semantic search, assistants, automation, and content generation tools
Develop, deploy, and maintain machine learning models for personalization, engagement prediction, churn, LTV forecasting, and fraud detection
Establish and enforce MLOps and data engineering best practices, ensuring model monitoring, retraining, and pipeline reliability
Implement scalable data infrastructure for experimentation, inference, and production workloads, including LLM pipelines and evaluation systems
Communicate complex modeling trade-offs clearly to technical and non-technical stakeholders
Technical Skills Required
Python PyTorch TensorFlow XGBoost Airflow dbt BigQuery Snowflake
Benefits & Perks
Opportunity to define and lead the data science and AI function with direct impact on products and business outcomes
Close collaboration with senior leadership and cross-functional product and engineering teams
Fully remote role with a structured time-off policy

Job Description


This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Head of Data in United Kingdom.

This role offers the opportunity to build and lead a data and AI function from the ground up within a fast-growing digital product environment. You will define the data strategy, deliver production-grade machine learning models, and establish a high-performing team. Working at the intersection of product, engineering, and analytics, your contributions will directly influence engagement, monetization, personalization, and risk controls. The role requires hands-on leadership, strategic vision, and the ability to translate complex data insights into actionable business outcomes. You will also guide the integration of AI/LLM capabilities into both product experiences and internal tools, ensuring scalable and impactful solutions across the organization.

Accountabilities

  • Define the vision and roadmap for the data function, prioritizing initiatives for maximum business impact.
  • Build, mentor, and manage a high-performing Data team while coordinating with external agencies until internal resources are established.
  • Partner with product, engineering, marketing, operations, and leadership to translate business goals into measurable outcomes.
  • Lead applied AI/LLM initiatives, including semantic search, assistants, automation, and content generation tools.
  • Develop, deploy, and maintain machine learning models for personalization, engagement prediction, churn, LTV forecasting, and fraud detection.
  • Establish and enforce MLOps and data engineering best practices, ensuring model monitoring, retraining, and pipeline reliability.
  • Implement scalable data infrastructure for experimentation, inference, and production workloads, including LLM pipelines and evaluation systems.
  • Communicate complex modeling trade-offs clearly to technical and non-technical stakeholders.

Requirements

  • 6+ years in Data Science or ML Engineering, with at least 2 years in senior leadership or ownership roles.
  • Strong Python skills and hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, XGBoost).
  • Proven experience deploying and operating ML models in production environments.
  • Expertise in one or more areas: recommendations/personalization, time-series forecasting, or fraud/risk modeling.
  • Familiarity with modern data stacks and pipeline tools (e.g., Airflow, dbt, BigQuery, Snowflake) and MLOps practices.
  • Strong experimentation mindset and ability to link modeling work to measurable business impact.
  • Excellent communication, strategic thinking, and leadership capabilities.

Benefits

  • Opportunity to define and lead the data science and AI function with direct impact on products and business outcomes.
  • Close collaboration with senior leadership and cross-functional product and engineering teams.
  • Fully remote role with a structured time-off policy including vacation, personal days, sick leave, parental leave, and local holidays.
  • Work in a fast-growing, innovative, and mission-driven digital product environment.

Why Apply Through Jobgether?

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.


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