Senior Data Scientist

Jobtailor; Greater London; On-site; GBP 80,000 - 120,000; Full time

Job summary

Jobtailor is seeking an experienced Data Scientist/ML Engineer to translate business challenges into scalable data products and production-ready models in a London-based role. You will own end-to-end projects from exploratory analysis to deployment, writing complex SQL and engineering features, and deploying baseline models while iterating toward more sophisticated solutions.

You will manage the full model lifecycle, collaborate with Engineering, Product, and Finance teams, and mentor junior

Qualifications

• 5+ years of applied experience in Data Science or ML Engineering.
• Track record of delivering production-ready models that drive measurable business value.
• Strong expertise in Python and SQL.
• Experience working in cloud-based environments such as AWS or GCP.
• Familiarity with CI/CD workflows, Git, and MLOps principles.
• Ability to connect technical metrics to business outcomes and select appropriate algorithms.
• Ability to explain technical concepts, model limitations, and analytical findings to non-technical stakeholders.
• BS/MS or equivalent experience in a quantitative field.

Responsibilities

• Translate complex business challenges into scalable data products and machine learning models.
• Own projects from exploratory analysis through production deployment.
• Write complex SQL and engineer features.
• Deploy baseline models quickly and iterate toward more complex solutions.
• Manage the complete model lifecycle, including data extraction, feature engineering, deployment, A/B testing, and performance monitoring.
• Partner with Engineering, Product, Business, and Finance stakeholders to define technical requirements and translate model outputs into actionable insights.
• Write clean, modular, production-ready code.
• Participate in peer code reviews and contribute to technical best practices.
• Break down ambiguous, complex requirements into executable milestones.
• Provide technical guidance to junior data scientists and analysts.

Skills

Python

SQL

Data Science

Machine Learning

EDA

Education

BS/MS

Tools

Pandas

NumPy

Scikit-Learn

PyTorch

XGBoost

LightGBM

Git

CI/CD

MLOps

Cloud Platforms

Job description

• Translate complex business challenges into scalable data products and machine learning models
• Own projects from exploratory analysis through production deployment
• Write complex SQL and engineer features
• Deploy baseline models quickly and iterate toward more complex solutions
• Manage the complete model lifecycle, including data extraction, feature engineering, deployment, A/B testing, and performance monitoring
• Partner with Engineering, Product, Business, and Finance stakeholders to define technical requirements and translate model outputs into actionable insights
• Write clean, modular, production-ready code
• Participate in peer code reviews and contribute to technical best practices
• Break down ambiguous, complex requirements into executable milestones
• Provide technical guidance to junior data scientists and analysts

Requirements

• 5+ years of applied experience in Data Science or ML Engineering
• Track record of delivering production-ready models that drive measurable business value
• Strong expertise in Python and SQL
• Deep familiarity with pandas, NumPy, scikit-learn, and standard ML frameworks such as PyTorch, XGBoost, or LightGBM
• Experience working in cloud-based environments such as AWS or GCP
• Familiarity with CI/CD workflows, Git, and MLOps principles
• Ability to connect technical metrics to business outcomes and select appropriate algorithms
• Ability to explain technical concepts, model limitations, and analytical findings to non-technical stakeholders
• BS, MS, or equivalent experience in a quantitative field
• Preferred: experience taking initial machine learning models from exploratory notebooks to automated production pipelines
• Preferred: experience in customer behavior and propensity modeling, forecasting, optimization, or causal inference

Core Competencies

Demonstrates expertise in Data Science and Machine Learning Engineering, with a strong focus on developing production-ready models that deliver measurable business value. Proficient in Python, SQL, and various ML frameworks, with the ability to translate complex data challenges into actionable insights for stakeholders.

Highest-signal resume keywords

• Python Programming
• SQL Proficiency
• Machine Learning Model Development
• Cloud-Based Environments (AWS, GCP)
• Data Lifecycle Management

Hard Skills

• Data Science
• Machine Learning Engineering
• Feature Engineering
• A/B Testing
• Performance Monitoring
• Model Deployment
• Exploratory Data Analysis
• Technical Documentation
• Algorithm Selection
• Statistical Analysis

Soft Skills

• Technical Communication
• Collaboration
• Mentoring
• Problem-Solving
• Adaptability

Industry Keywords

• Data Products
• Business Insights
• Customer Behavior Modeling
• Forecasting
• Optimization
• Causal Inference

Tools & Technologies

• Pandas
• NumPy
• Scikit-Learn
• PyTorch
• XGBoost
• LightGBM
• Git
• CI/CD Workflows
• MLOps Principles
• Cloud Platforms