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Lead Forensics
Marketing & Advertising
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Lead Forensics is at the forefront of building the next generation of B2B buyer intelligence. By integrating behavioural, engagement, firmographic, and intent signals, we empower our customers to identify in-market opportunities, understand prospect behaviour, and make better commercial decisions. Our platform processes vast amounts of data, leveraging advanced analytics, machine learning, and AI to transform fragmented signals into actionable and trusted intelligence.
We're seeking an experienced Senior Data Scientist (minimum 5 years experience) to join our expanding Data & AI team. In this pivotal role, you will develop innovative data products, predictive models, and intelligent signals to help our customers discover opportunities, recognise buying intent, and act faster than their competitors.
The ideal candidate will combine robust data science expertise with strong product instincts. You are comfortable working with large-scale time-series and event-stream data, uncovering valuable signals from noise, and delivering production-ready solutions that can be embedded across our SaaS platforms.
This role suits a hands-on, senior individual contributor who thrives on moving from experimentation to real-world impact, turning data-driven concepts into measurable business results.
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.
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.
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
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Marcus Rivera
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