Senior Data Scientist

Summary

Data Science & Machine Learning

Data Products & Platform Integration

AI & Advanced Analytics

Data Strategy & Leadership

Experience & Background

Technical Strength

Mindset & Working Style

What Success Looks Like

Why Join Lead Forensics?

What We Offer

• Competitive salary, commensurate with experience and seniority
• 25 days’ holiday, plus bank holidays, and your birthday off
• Attractive office location near Portsmouth
• Fantastic company culture, built on our "One Team" and "Growth" values
• Opportunities to give back through volunteer days, fundraisers, and charity events
• Regular company socials, team-building activities, and cross-functional events
• Free on-site parking and gym
• Two paid charity days per year

Qualifications

• Experience & Background
• 5+ years of experience in Data Science, Machine Learning, Applied AI, or a similar discipline.
• Strong academic background in Mathematics, Statistics, Computer Science, Data Science, Physics, Engineering, or a related quantitative field.
• Substantial experience working with large-scale, event-driven datasets.
• Proven track record of deploying production ML solutions that create measurable business value.
• Experience in SaaS, AdTech, MarTech, Sales Intelligence, Consumer Analytics, or similar data-intensive fields.
• Technical Strength
• Excellent Python development skills.
• Deep understanding of statistics and machine learning theory.
• Experience with supervised, unsupervised, and probabilistic modelling.
• Advanced SQL skills and experience working with large datasets.
• Demonstrated ability to create data products, not just deliver analyses.
• Familiarity with modern cloud-native data platforms and scalable ML infrastructure.
• Understanding of MLOps practices, including model versioning, monitoring, and deployment workflows.
• Strong grasp of experimentation, hypothesis testing, and causal inference.
• Mindset & Working Style
• Commercially focused and results-driven.
• Curious, creative, and motivated by solving complex problems.
• Comfortable switching between research, experimentation, and production delivery.
• Able to clearly communicate complex ideas to technical and non-technical stakeholders.
• Effective collaborator who enjoys working across Product, Engineering, and Data teams.
• Passionate about building impactful, customer-focused solutions.
• What Success Looks Like
• Launching new predictive signals that directly enhance customer outcomes.
• Increasing the quality and reliability of behavioural insights on our platform.
• Establishing repeatable, robust processes for model evaluation and deployment.
• Building strong partnerships with Product and Engineering teams.
• Creating reusable data products leveraged by multiple services at Lead Forensics.
• Helping to shape the organisation’s AI-powered product capabilities.
• Why Join Lead Forensics?
• Build data products that drive how thousands of customers identify opportunities and understand buying intent.
• Own projects from research to production, making a visible business impact.
• Work closely with Product, Engineering, and Leadership to drive innovation across the platform.
• Collaborate with skilled software engineers to deliver robust, scalable ML solutions—not just isolated analytical models.
• Influence the shape of our data and AI strategy while remaining hands-on with the latest technologies.
• Enjoy a remote-first culture, with occasional collaborative sessions at our Portsmouth office.

Responsibilities

• Develop predictive models that identify patterns, opportunities, risks, and trends from large volumes of visitor activity data.
• Design and implement machine learning techniques that transform noisy behavioural data into commercially valuable insights.
• Build time-series models to detect trends, anomalies, seasonality, intent signals, and shifts in customer behaviour.
• Create ranking, scoring, recommendation, and propensity models for customer engagement and sales intelligence.
• Apply statistical methods to assess signal quality, confidence, uncertainty, and the reliability of models.
• Continually evaluate and enhance model performance using real-world data.
• Design models and analytics as reusable data products, not just one-off analyses.
• Collaborate with software engineers to productionise models via APIs, services, event streams, and platform integration.
• Develop data contracts and interfaces for seamless consumption of machine learning outputs by engineering teams.
• Work with Product Managers to define and prioritise data-driven features.
• Ensure models are observable, reproducible, monitorable, and maintainable, with robust performance tracking and continuous improvement.
• Investigate cutting-edge AI techniques, including agentic workflows, to drive improved customer outcomes and productivity.
• Identify where large language models (LLMs) and structured behavioural signals can be combined to add value.
• Create robust evaluation frameworks and guardrails for AI-powered solutions.
• Drive a spirit of experimentation while focusing on tangible, measurable business outcomes.
• Influence Lead Forensics’ approach to data science, experimentation, and machine learning.
• Champion evidence-based decision making within Product and Engineering.
• Help establish best practices for model lifecycle management, feature engineering, experimentation, and reproducibility.
• Contribute to the long-term vision for the company’s data and AI capabilities.
• About You
• 5+ years of experience in Data Science, Machine Learning, Applied AI, or a similar discipline.
• Strong academic background in Mathematics, Statistics, Computer Science, Data Science, Physics, Engineering, or a related quantitative field.
• Substantial experience working with large-scale, event-driven datasets.
• Proven track record of deploying production ML solutions that create measurable business value.
• Experience in SaaS, AdTech, MarTech, Sales Intelligence, Consumer Analytics, or similar data-intensive fields.
• Excellent Python development skills.
• Deep understanding of statistics and machine learning theory.
• Experience with supervised, unsupervised, and probabilistic modelling.
• Advanced SQL skills and experience working with large datasets.
• Demonstrated ability to create data products, not just deliver analyses.
• Familiarity with modern cloud-native data platforms and scalable ML infrastructure.
• Understanding of MLOps practices, including model versioning, monitoring, and deployment workflows.
• Strong grasp of experimentation, hypothesis testing, and causal inference.
• Commercially focused and results-driven.
• Curious, creative, and motivated by solving complex problems.
• Comfortable switching between research, experimentation, and production delivery.
• Able to clearly communicate complex ideas to technical and non-technical stakeholders.
• Effective collaborator who enjoys working across Product, Engineering, and Data teams.
• Passionate about building impactful, customer-focused solutions.
• Launching new predictive signals that directly enhance customer outcomes.
• Increasing the quality and reliability of behavioural insights on our platform.
• Establishing repeatable, robust processes for model evaluation and deployment.
• Building strong partnerships with Product and Engineering teams.
• Creating reusable data products leveraged by multiple services at Lead Forensics.
• Helping to shape the organisation’s AI-powered product capabilities.
• Build data products that drive how thousands of customers identify opportunities and understand buying intent.
• Own projects from research to production, making a visible business impact.
• Work closely with Product, Engineering, and Leadership to drive innovation across the platform.
• Collaborate with skilled software engineers to deliver robust, scalable ML solutions—not just isolated analytical models.
• Influence the shape of our data and AI strategy while remaining hands-on with the latest technologies.
• Enjoy a remote-first culture, with occasional collaborative sessions at our Portsmouth office.