Senior Data Scientist
Posted Updated
Description
- 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
- 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
- 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
- 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
- Usual working days for LF are 5 days a week, Monday- Friday
- We’re seeking an experienced Senior Data Scientist (minimum 5 years experience) to join our expanding Data & AI team
- 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
- 5+ years of experience in Data Science, Machine Learning, Applied AI, or a similar discipline
- Experience in SaaS, AdTech, MarTech, Sales Intelligence, Consumer Analytics, or similar data-intensive fields
- Substantial experience working with large-scale, event-driven datasets
- Proven track record of deploying production ML solutions that create measurable business value
- Strong academic background in Mathematics, Statistics, Computer Science, Data Science, Physics, Engineering, or a related quantitative field
- Deep understanding of statistics and machine learning theory
- Understanding of MLOps practices, including model versioning, monitoring, and deployment workflows
- Strong grasp of experimentation, hypothesis testing, and causal inference
- Excellent Python development skills
- Familiarity with modern cloud-native data platforms and scalable ML infrastructure
- Advanced SQL skills and experience working with large datasets
- Demonstrated ability to create data products, not just deliver analyses
- Experience with supervised, unsupervised, and probabilistic modelling
- 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
- Passionate about building impactful, customer-focused solutions
- Effective collaborator who enjoys working across Product, Engineering, and Data teams
- Commercially focused and results-driven