Senior Data Scientist

Lead Forensics; United States; Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

25 days’ holiday

Remote-first culture

Occasional Portsmouth office sessions

Gym on-site perks

Job summary

Lead Forensics is seeking a Senior Data Scientist to build predictive signals and production-ready AI capabilities. You will work across Data Science, Product, and Engineering to deliver data-driven features and scalable ML solutions that enhance buyer intelligence for B2B customers.

The role emphasizes experimentation, production deployment, and collaboration with cross-functional teams in a remote-first environment, with occasional Portsmouth office engagement.

Qualifications

• Minimum 5 years in Data Science, ML, or applied AI.
• Strong background in mathematics, statistics, CS or related field.
• Experience with large-scale, event-driven datasets and production ML solutions.
• Experience in SaaS, AdTech, MarTech, or data-intensive domains.
• Proven ability to deploy models that deliver business value.

Responsibilities

• Develop predictive models to identify patterns, opportunities, risks, and trends.
• Design ML techniques to transform noisy data into insights.
• Build time-series models for trends, anomalies, and intent signals.
• Create data products and collaborate with engineers to productionise models via APIs.
• Ensure observability, reproducibility, and monitoring of models.

Skills

Python

Statistics

ML theory

Experimentation

Communication

Cross-functional collaboration

Education

Quantitative degree (Math/CS/Stats)

Tools

SQL

Cloud platforms

MLOps tools

Job description

Senior Data Scientist

Summary

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.

Key Responsibilities

Data Science & Machine Learning

• 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.

Data Products & Platform Integration

• 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.

AI & Advanced Analytics

• 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.

Data Strategy & Leadership

• 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

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.

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